{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "aEJv_ZkwEGba"
   },
   "source": [
    "<center>\n",
    "    <p style=\"text-align:center\">\n",
    "        <img alt=\"phoenix logo\" src=\"https://storage.googleapis.com/arize-assets/arize-logo-white.jpg\" width=\"200\"/>\n",
    "        <br>\n",
    "        <img alt=\"phoenix logo\" src=\"https://storage.googleapis.com/arize-assets/phoenix/assets/phoenix-logo-light.svg\" width=\"200\"/>\n",
    "        <br>\n",
    "        <a href=\"https://arize.com/docs/phoenix/\">Docs</a>\n",
    "        |\n",
    "        <a href=\"https://github.com/Arize-ai/phoenix\">GitHub</a>\n",
    "        |\n",
    "        <a href=\"https://arize-ai.slack.com/join/shared_invite/zt-2w57bhem8-hq24MB6u7yE_ZF_ilOYSBw#/shared-invite/email\">Community</a>\n",
    "    </p>\n",
    "</center>\n",
    "<h1 align=\"center\">Agent Tool Selection Classification Evals</h1>\n",
    "\n",
    "The purpose of this notebook is:\n",
    "\n",
    "- to evaluate the performance of an LLM-assisted approach to evaluating agent tool selection,\n",
    "- to provide an experimental framework for users to iterate and improve on the default agent tool calling template.\n",
    "\n",
    "## Install Dependencies and Import Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "0la5vhfxEGbb",
    "outputId": "dc31c43e-20e0-4a2d-fdbe-a3c8b7c135ac"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "google-genai 1.24.0 requires httpx<1.0.0,>=0.28.1, but you have httpx 0.27.2 which is incompatible.\n",
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   ],
   "source": [
    "%pip install -qq \"arize-phoenix-evals>=0.22.0\" \"openai>=1\" ipython matplotlib pycm pyarrow opentelemetry-sdk scikit-learn arize tiktoken nest_asyncio 'httpx<0.28'\n",
    "%pip install \"arize[Datasets]\" opentelemetry-sdk\n",
    "%pip install openai pandas\n",
    "%pip install \"anthropic>=0.18.0\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "UX492hfvEGbb"
   },
   "source": [
    "ℹ️ To enable async request submission in notebook environments like Jupyter or Google Colab, optionally use `nest_asyncio`. `nest_asyncio` globally patches `asyncio` to enable event loops to be re-entrant. This is not required for non-notebook environments.\n",
    "\n",
    "Without `nest_asyncio`, eval submission can be much slower, depending on your organization's rate limits. Speed increases of about 5x are typical."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "OKTub2q4EGbc"
   },
   "outputs": [],
   "source": [
    "import nest_asyncio\n",
    "\n",
    "nest_asyncio.apply()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "5N4dMv_1EGbc"
   },
   "outputs": [],
   "source": [
    "import json\n",
    "import os\n",
    "from getpass import getpass\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import openai\n",
    "import pandas as pd\n",
    "from pycm import ConfusionMatrix\n",
    "\n",
    "pd.set_option(\"display.max_colwidth\", None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Gthqcv8xEGbc"
   },
   "source": [
    "## Download Benchmark Dataset\n",
    "\n",
    "We'll evaluate the evaluation system consisting of a few example user prompts, with corresponding tool choices and ground truth answers, in addition to an evaluation prompt template against benchmark datasets of user queries and the corresponding tools called with ground-truth labels. We will be using the Berkely Function-Calling Leaderboard dataset. This dataset is commonly used for Agent applications that call tools as a benchmark."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "a5mv7s5zPpTu",
    "outputId": "86ad9347-09d7-43db-c42d-b2c7e9126955"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2025-07-10 16:15:44--  https://huggingface.co/datasets/gorilla-llm/Berkeley-Function-Calling-Leaderboard/blob/main/BFCL_v3_exec_multiple.json\n",
      "Resolving huggingface.co (huggingface.co)... 3.166.152.44, 3.166.152.65, 3.166.152.110, ...\n",
      "Connecting to huggingface.co (huggingface.co)|3.166.152.44|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 1201626 (1.1M) [text/html]\n",
      "Saving to: ‘exec_simple.json’\n",
      "\n",
      "exec_simple.json    100%[===================>]   1.15M  --.-KB/s    in 0.1s    \n",
      "\n",
      "2025-07-10 16:15:44 (11.3 MB/s) - ‘exec_simple.json’ saved [1201626/1201626]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!wget -O exec_simple.json https://huggingface.co/datasets/gorilla-llm/Berkeley-Function-Calling-Leaderboard/blob/main/BFCL_v3_exec_multiple.json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "FW2qxwM2P0sh",
    "outputId": "99a28f09-2c62-4524-8b8b-3a334d56f72f"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import requests\n",
    "\n",
    "# Load dataset\n",
    "url = \"https://huggingface.co/datasets/gorilla-llm/Berkeley-Function-Calling-Leaderboard/resolve/main/BFCL_v3_exec_multiple.json\"\n",
    "response = requests.get(url)\n",
    "dataset = [json.loads(line) for line in response.text.strip().splitlines()]\n",
    "\n",
    "# Collect all unique tool definitions (these are all the tools the agent can choose from)\n",
    "unique_tools = {}\n",
    "for entry in dataset:\n",
    "    for tool in entry.get(\"function\", []):\n",
    "        if tool[\"name\"] not in unique_tools:\n",
    "            unique_tools[tool[\"name\"]] = tool\n",
    "\n",
    "tool_definitions_text = \"\\n\".join(\n",
    "    f\"{tool['name']}: {tool['description']} | Parameters: {json.dumps(tool['parameters'])}\"\n",
    "    for tool in unique_tools.values()\n",
    ")\n",
    "\n",
    "\n",
    "# Prepare data for evaluation\n",
    "eval_data = []\n",
    "for entry in dataset:\n",
    "    question = entry[\"question\"][0][0][\"content\"]\n",
    "    ground_truths = entry.get(\"ground_truth\", [])\n",
    "    for gt in ground_truths:\n",
    "        eval_data.append(\n",
    "            {\"question\": question, \"tool_call\": gt, \"tool_definitions\": tool_definitions_text}\n",
    "        )\n",
    "\n",
    "df_eval = pd.DataFrame(eval_data)\n",
    "df_eval.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "eO7_Lz5iSxnt"
   },
   "source": [
    "## Modify Benchmark Dataset\n",
    "\n",
    "The BFCL Dataset does not have any `negative` examples, i.e. only `question`, `available_tools`, and `ground_truth` are present. In order to accurately benchmark our LLM-as-a-Judge, this code snippet appends some `incorrect` examples to our dataset, by adding 20 rows of data where the `incorrect` tool is selected."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "id": "TnUiOiwYS31x"
   },
   "outputs": [],
   "source": [
    "import json\n",
    "import random\n",
    "import re\n",
    "\n",
    "\n",
    "# Parse tool definitions into a dict: tool_name -> list of required parameters\n",
    "def extract_tool_param_templates(tool_definitions):\n",
    "    tools = {}\n",
    "    pattern = r\"^(\\w+):.*?\\| Parameters: (.*)$\"\n",
    "    for line in tool_definitions.strip().split(\"\\n\"):\n",
    "        match = re.match(pattern, line.strip())\n",
    "        if match:\n",
    "            name, param_json = match.groups()\n",
    "            try:\n",
    "                param_schema = json.loads(param_json)\n",
    "                required = param_schema.get(\"required\", [])\n",
    "                tools[name] = required\n",
    "            except json.JSONDecodeError:\n",
    "                continue\n",
    "    return tools\n",
    "\n",
    "\n",
    "tool_param_templates = extract_tool_param_templates(tool_definitions_text)\n",
    "tool_names = list(tool_param_templates.keys())\n",
    "\n",
    "# Sample 20 wrong examples\n",
    "wrong_examples = []\n",
    "for i in range(20):\n",
    "    row = df_eval.iloc[i]\n",
    "    question = row[\"question\"]\n",
    "    correct_tool_call_str = row[\"tool_call\"]\n",
    "\n",
    "    # Get correct tool name (assume it's before the first '(')\n",
    "    try:\n",
    "        correct_tool_name = correct_tool_call_str.split(\"(\")[0]\n",
    "    except Exception as e:\n",
    "        print(f\"Skipping row {i} due to error: {e}\")\n",
    "        continue\n",
    "\n",
    "    # Get a different tool\n",
    "    incorrect_tools = [tool for tool in tool_names if tool != correct_tool_name]\n",
    "    if not incorrect_tools:\n",
    "        continue\n",
    "\n",
    "    wrong_tool = random.choice(incorrect_tools)\n",
    "    required_params = tool_param_templates.get(wrong_tool, [])\n",
    "\n",
    "    # Build dummy argument string\n",
    "    dummy_args = []\n",
    "    for param in required_params:\n",
    "        dummy_value = random.choice(\n",
    "            [42, 3.14, '\"example\"', \"[1, 2, 3]\", \"True\"]\n",
    "        )  # random but plausible\n",
    "        dummy_args.append(f\"{param}={dummy_value}\")\n",
    "\n",
    "    wrong_tool_call = f\"{wrong_tool}({', '.join(dummy_args)})\"\n",
    "\n",
    "    wrong_examples.append(\n",
    "        {\n",
    "            \"question\": question,\n",
    "            \"tool_call\": wrong_tool_call,\n",
    "            \"tool_definitions\": tool_definitions_text,\n",
    "        }\n",
    "    )\n",
    "\n",
    "# Create and label the correct examples\n",
    "df_eval[\"true_label\"] = \"correct\"\n",
    "\n",
    "# Create and label the incorrect examples\n",
    "df_wrong = pd.DataFrame(wrong_examples)\n",
    "df_wrong[\"true_label\"] = \"incorrect\"\n",
    "\n",
    "# Combine both datasets\n",
    "df_combined = pd.concat([df_eval, df_wrong], ignore_index=True)\n",
    "\n",
    "# OPTIONAL: Shuffle AFTER labeling\n",
    "df_eval_final = df_combined.sample(frac=1).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "1BsKhwkqEGbc"
   },
   "source": [
    "## Display Agent Tool Selection Prompt Template\n",
    "\n",
    "View the default template used to evaluate agent tool calling. You can tweak this template and evaluate its performance relative to the default."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "mbuxlKUqlvk0",
    "outputId": "8041815e-a941-45f7-c878-db81640ef717"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "You are an evaluation assistant assessing whether a tool call correctly matches a user's question. \n",
      "Your task is to decide if the tool selected is the best choice to answer the question,\n",
      "using only the list of available tools provided below. You are not responsible for checking the \n",
      "parameters or arguments passed to the tool. You are evaluating **only** whether the correct tool \n",
      "was selected based on the content of the question. Think like a grading rubric. Be strict. If the\n",
      "selected tool is not clearly correct based on the question alone, label it \"incorrect\". Do not \n",
      "make assumptions or infer information that is not explicitly stated in the question. \n",
      "Only use the information provided.\n",
      "\n",
      "Your response must be a **single word**: either `\"correct\"` or `\"incorrect\"`. \n",
      "Do not include any explanation, punctuation, or other characters. The output will be parsed\n",
      "programmatically.\n",
      "\n",
      "---\n",
      "\n",
      "Label the tool call as `\"correct\"` if **all** of the following are true:\n",
      "- The selected tool is clearly the best fit to answer the user's question\n",
      "- The tool is among those available in the tool list\n",
      "- The question contains enough explicit information to justify selecting this tool\n",
      "\n",
      "Label the tool call as `\"incorrect\"` if **any** of the following are true:\n",
      "- A more appropriate tool exists to answer the question\n",
      "- The tool is not clearly justified by the question content\n",
      "- The tool would not produce a relevant or meaningful answer to the question\n",
      "\n",
      "---\n",
      "\n",
      "[BEGIN DATA]\n",
      "************\n",
      "[Question]: {question}\n",
      "************\n",
      "[Tool Called]: {tool_call}\n",
      "[END DATA]\n",
      "\n",
      "[Tool Definitions]: {tool_definitions}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "TOOL_SELECTION_PROMPT_TEMPLATE = \"\"\"\n",
    "You are an evaluation assistant assessing whether a tool call correctly matches a user's question.\n",
    "Your task is to decide if the tool selected is the best choice to answer the question,\n",
    "using only the list of available tools provided below. You are not responsible for checking the\n",
    "parameters or arguments passed to the tool. You are evaluating **only** whether the correct tool\n",
    "was selected based on the content of the question. Think like a grading rubric. Be strict. If the\n",
    "selected tool is not clearly correct based on the question alone, label it \"incorrect\". Do not\n",
    "make assumptions or infer information that is not explicitly stated in the question.\n",
    "Only use the information provided.\n",
    "\n",
    "Your response must be a **single word**: either `\"correct\"` or `\"incorrect\"`.\n",
    "Do not include any explanation, punctuation, or other characters. The output will be parsed\n",
    "programmatically.\n",
    "\n",
    "---\n",
    "\n",
    "Label the tool call as `\"correct\"` if **all** of the following are true:\n",
    "- The selected tool is clearly the best fit to answer the user's question\n",
    "- The tool is among those available in the tool list\n",
    "- The question contains enough explicit information to justify selecting this tool\n",
    "\n",
    "Label the tool call as `\"incorrect\"` if **any** of the following are true:\n",
    "- A more appropriate tool exists to answer the question\n",
    "- The tool is not clearly justified by the question content\n",
    "- The tool would not produce a relevant or meaningful answer to the question\n",
    "\n",
    "---\n",
    "\n",
    "[BEGIN DATA]\n",
    "************\n",
    "[Question]: {question}\n",
    "************\n",
    "[Tool Called]: {tool_call}\n",
    "[END DATA]\n",
    "\n",
    "[Tool Definitions]: {tool_definitions}\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "oR2oNMS6EGbc"
   },
   "source": [
    "Eval template variables:\n",
    "\n",
    "- **question** : The question the user poses\n",
    "- **tool_call** : The tool that is actually called (ground truth)\n",
    "- **tool_definitions** : All the available tools to the agent"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "tV3bLwrAEGbd"
   },
   "source": [
    "## Configure the LLM\n",
    "\n",
    "Configure your API keys."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "dlm4HdAGEGbd",
    "outputId": "9ac7a166-774c-4bee-aa5c-9094622c93c7"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🔑 Enter your OpenAI API key: ··········\n",
      "🔑 Enter your Anthropic API key: ··········\n"
     ]
    }
   ],
   "source": [
    "if not (openai_api_key := os.getenv(\"OPENAI_API_KEY\")):\n",
    "    openai_api_key = getpass(\"🔑 Enter your OpenAI API key: \")\n",
    "\n",
    "openai.api_key = openai_api_key\n",
    "os.environ[\"OPENAI_API_KEY\"] = openai_api_key\n",
    "\n",
    "\n",
    "# Set Anthropic API key\n",
    "if not (anthropic_api_key := os.getenv(\"ANTHROPIC_API_KEY\")):\n",
    "    anthropic_api_key = getpass(\"🔑 Enter your Anthropic API key: \")\n",
    "\n",
    "os.environ[\"ANTHROPIC_API_KEY\"] = anthropic_api_key"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "9NJpkArqgrmE"
   },
   "source": [
    "## Evaluate the Dataset Using Phoenix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 903,
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      "5ed2aed7fd4a40a5a7fb7a2bf22b016b",
      "0a9e6319b3314a0c820c36a6b0ce9366"
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    },
    "id": "q5zDDCXqPwN0",
    "outputId": "fcd816cc-1d09-4936-bb90-9102b1fc6ae2"
   },
   "outputs": [],
   "source": [
    "from tqdm import tqdm\n",
    "\n",
    "from phoenix.evals import (\n",
    "    create_classifier,\n",
    "    evaluate_dataframe,\n",
    ")\n",
    "from phoenix.evals.llm import LLM\n",
    "\n",
    "# List of OpenAI model codes to benchmark\n",
    "open_ai_models = [\n",
    "    \"gpt-4o\",  # GPT-4 Omni (May 2024)\n",
    "    \"gpt-4o-mini\",  # Smaller version of GPT-4o\n",
    "    \"gpt-4\",  # GPT-4 (March 2023)\n",
    "    \"gpt-4-turbo\",  # GPT-4 Turbo (November 2023)\n",
    "    \"gpt-4-turbo-2024-04-09\",  # GPT-4 Turbo snapshot (April 2024)\n",
    "    \"gpt-3.5-turbo\",  # GPT-3.5 Turbo (March 2023)\n",
    "    \"gpt-3.5-turbo-0125\",  # GPT-3.5 Turbo snapshot (January 2025)\n",
    "    \"o1\",  # OpenAI's first reasoning model\n",
    "    \"o1-mini\",  # Smaller version of o1\n",
    "    \"o3\",  # Successor to o1 with improved reasoning\n",
    "    \"o3-mini\",  # Smaller version of o3\n",
    "    \"o4-mini\",  # Latest mini reasoning model (April 2025)\n",
    "]\n",
    "\n",
    "\n",
    "all_results = []\n",
    "\n",
    "# ---------- Evaluate OpenAI Models ----------\n",
    "for model_name in tqdm(open_ai_models):\n",
    "    print(f\"\\n🧪 Evaluating OpenAI model: {model_name}\")\n",
    "\n",
    "    model = LLM(provider=\"openai\", model=model_name)\n",
    "\n",
    "    tool_select_eval = create_classifier(\n",
    "        name=\"tool selection extraction\",\n",
    "        prompt_template=TOOL_SELECTION_PROMPT_TEMPLATE,\n",
    "        llm=model,\n",
    "        choices={\"correct\": 1.0, \"incorrect\": 0.0},\n",
    "    )\n",
    "\n",
    "    results_df = evaluate_dataframe(dataframe=df_eval, evaluators=[tool_select_eval])\n",
    "\n",
    "    results_df[\"label\"] = results_df[\"tool selection extraction_score\"].apply(\n",
    "        lambda x: x.get(\"label\") if isinstance(x, dict) else None\n",
    "    )\n",
    "    results_df[\"model\"] = results_df[\"tool selection extraction_score\"].apply(\n",
    "        lambda x: x.get(\"metadata\").get(\"model\") if isinstance(x, dict) else None\n",
    "    )\n",
    "    all_results.append(results_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "sNF3fP4QcFs7"
   },
   "source": [
    "## Evaluate Anthropic Models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 373,
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      "c625226447ff4b66b760aada61e51198",
      "6c38128fb4ac4fa48359ce0c108d2465",
      "811648e0bd6f4845bed8aa78c6b37bd5"
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    },
    "id": "LJX1KXX2cE_v",
    "outputId": "f5d21bd2-bea1-4394-9f75-d7412a6a7c8c"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r  0%|          | 0/5 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "🧪 Evaluating Anthropic model: claude-3-opus-20240229\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e3e25b820390495da81b363998884548",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "llm_classify |          | 0/50 (0.0%) | ⏳ 00:00<? | ?it/s"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r 20%|██        | 1/5 [00:22<01:29, 22.33s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "🧪 Evaluating Anthropic model: claude-3-sonnet-20240229\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "63331f1392644af4b6725242a657902f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "llm_classify |          | 0/50 (0.0%) | ⏳ 00:00<? | ?it/s"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r 40%|████      | 2/5 [00:35<00:51, 17.12s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "🧪 Evaluating Anthropic model: claude-3-haiku-20240307\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "647ecf4e504249bc8b6090439f349913",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "llm_classify |          | 0/50 (0.0%) | ⏳ 00:00<? | ?it/s"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r 60%|██████    | 3/5 [00:51<00:32, 16.42s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "🧪 Evaluating Anthropic model: claude-opus-4-20250514\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fdfd34ae56c84076bda56b132ed1055c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "llm_classify |          | 0/50 (0.0%) | ⏳ 00:00<? | ?it/s"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r 80%|████████  | 4/5 [01:05<00:15, 15.64s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "🧪 Evaluating Anthropic model: claude-sonnet-4-20250514\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a510f9330d944a04a5bc0ffc613dedca",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "llm_classify |          | 0/50 (0.0%) | ⏳ 00:00<? | ?it/s"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 5/5 [01:20<00:00, 16.13s/it]\n"
     ]
    }
   ],
   "source": [
    "# ---------- Evaluate Anthropic Models ----------\n",
    "# List of Claude (Anthropic) models to benchmark\n",
    "anthropic_models = [\n",
    "    \"claude-3-opus-20240229\",  # Claude 3 Opus\n",
    "    \"claude-3-sonnet-20240229\",  # Claude 3 Sonnet\n",
    "    \"claude-3-haiku-20240307\",  # Claude 3 Haiku\n",
    "    \"claude-opus-4-20250514\",  # Claude Opus 4\n",
    "    \"claude-sonnet-4-20250514\",  # Claude Sonnet 4\n",
    "]\n",
    "\n",
    "for model_name in tqdm(anthropic_models):\n",
    "    print(f\"\\n🧪 Evaluating Anthropic model: {model_name}\")\n",
    "\n",
    "    model = LLM(provider=\"anthropic\", model=model_name)\n",
    "\n",
    "    tool_select_eval = create_classifier(\n",
    "        name=\"tool selection extraction\",\n",
    "        prompt_template=TOOL_SELECTION_PROMPT_TEMPLATE,\n",
    "        llm=model,\n",
    "        choices={\"correct\": 1.0, \"incorrect\": 0.0},\n",
    "    )\n",
    "\n",
    "    results_df = evaluate_dataframe(dataframe=df_eval, evaluators=[tool_select_eval])\n",
    "\n",
    "    results_df[\"label\"] = results_df[\"tool selection extraction_score\"].apply(\n",
    "        lambda x: x.get(\"label\") if isinstance(x, dict) else None\n",
    "    )\n",
    "    results_df[\"model\"] = results_df[\"tool selection extraction_score\"].apply(\n",
    "        lambda x: x.get(\"metadata\").get(\"model\") if isinstance(x, dict) else None\n",
    "    )\n",
    "    all_results.append(results_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Z7W3RD-yUrvR"
   },
   "source": [
    "## Show Results\n",
    "\n",
    "Let's see how well different models performed as a Judge! We'll show:\n",
    "- Confusion Matrix for one model (GPT 4o)\n",
    "- F1 score per model benchmarked, to compare how different models perform as a judge vs the ground truth\n",
    "-  An agreement matrix to see which models agree with each other as judges."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "MEZEr0cVUu9Z",
    "outputId": "c7041ae3-8bbf-4d84-e78a-5b485d7ba086"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipython-input-12-2317285331.py:48: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  ax = sns.barplot(\n"
     ]
    },
    {
     "data": {
      "image/png": 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338HPz0/hPjt37sS4ceMwYsQIhb6tUoa///4b6urq0NPTUyi+trYWN27cQLt27aCmptZkfFlZGQwMDLAxJZPv6SYiIiIiesTdijsIHOSC0tJS6OvrK9RHkbrjo48+QmJiIs6cOSO0jR07Frdv30ZSUhIAwN3dHb169UJsbCwAQCqVwsrKCjNnzkRYWJjC18CZbnpmFRQUYM6cOXj11VdbNQ8jIyOFC24AUFVVhZmZmUIFNxERERERPX3p6enw9vaWa/Px8UF6ejoAoKqqCpmZmXIxKioq8Pb2FmIUxaKbFFJeXo7x48dDR0cH5ubmWL16tdyya4lEgqVLl2LcuHHQ0dGBpaWl3NIOiUQCABg5ciREIpGw35Da2lqMHz8eixcvho2NTZ3j//zzDyZMmIA2bdpAW1sbvr6+OHfuXKNjHjp0CCKRCMnJyejRowfEYjEGDBiA69ev46effoKDgwP09fXx9ttv4+7du0K/fy8vl0gkWL58OSZNmgQ9PT1YW1vjq6++Eo5zeTkRERER0bOtuLgYpqamcm2mpqYoKyvDvXv3cPPmTdTW1tYbU1xc3KxzsegmhYSEhCAtLQ379+9HSkoKjh49iqysLLmYFStWwMnJCdnZ2QgLC8MHH3yAlJQUAEBGRgYAYPPmzSgqKhL2G7JkyRKYmJggMDCw3uMTJ07EqVOnsH//fqSnp0Mmk2HIkCGorq5u8loWLVqE2NhY/Prrr7hy5QpGjx6NmJgY7NixA4mJifj555+xdu3aRsdYtWoVXF1dkZ2djenTp2PatGnIz89v8twAUFlZibKyMrmNiIiIiIheTFz/Sk0qLy/Hli1bsGPHDgwcOBDAg+LZwsJCLs7T01O4t+GVV15BWloaVq9ejUGDBsHY2BgAYGhoCDMzs0bPd+zYMWzcuLHBmeJz585h//79SEtLQ+/evQEA27dvh5WVFfbt24e33nqr0fE//vhjeHp6AgACAwMRHh6OCxcuCDPqb775Jn755Rd89NFHDY4xZMgQTJ8+HcCD+0FWr16NX375Bfb29o2eGwAiIyOxePHiJuOIiIiIiEg5zMzMUFJSItdWUlICfX19iMViqKqqQlVVtd6YpuqZf+NMNzXp4sWLqK6uhpubm9BmYGBQp8D08PCos5+Xl9fguIWFhdDV1RW25cuXo7y8HO+++y7Wr1+Pdu3a1dsvLy8PampqcHd3F9ratm0Le3t74Xy+vr7CuF26dJHr3717d+HPpqam0NbWllvCbmpq2uQTCR8dQyQSwczMTOGnGIaHh6O0tFTYrly5olA/IiIiIiJqGR4eHkhNTZVrS0lJEWoaDQ0NuLi4yMVIpVKkpqbWqXuawpluajUWFhZys9lGRka4cOECCgoKMHz4cKFdKpUCANTU1BRewr1hwwbcu3cPAKCuri537NF9kUhU57hIJBLO2ZDH6fOQpqYmNDU1FYolIiIiIqKm3blzB+fPnxf2L126hJycHBgZGcHa2hrh4eG4evUqtm7dCgCYOnUqYmNjERoaikmTJuHgwYP45ptvkJiYKIwREhICf39/uLq6ws3NDTExMaioqEBAQECzcmPRTU2ysbGBuro6MjIyYG1tDQAoLS3Fn3/+ib59+wpxx48fl+t3/PhxODg4CPvq6uqora0V9tXU1GBnZyfXR1tbG6dPn5Zrmz9/PsrLy7FmzRpYWVlBKpWipqYGJ06cEJaX37p1C/n5+XB0dAQAWFpatsCVExERERHR8+DUqVPo37+/sB8SEgIA8Pf3R3x8PIqKilBYWCgc79ixIxITEzF79mysWbMG7du3x4YNG+Dj4yPEjBkzBjdu3MDChQtRXFwMZ2dnJCUl1Xm4WlNYdFOT9PT04O/vj7lz58LIyAgmJiaIiIiAiooKRCKREJeWloaoqCj4+fkhJSUFu3fvlvumSCKRIDU1FZ6entDU1ESbNm3qnEtLSwtdu3aVazM0NAQAob1Tp04YMWIEpkyZgi+//BJ6enoICwuDpaUlRowYoYRPgIiIiIiInmVeXl6QyWQNHo+Pj6+3T3Z2dqPjBgUFISgo6Ily4z3dpJDo6Gh4eHhg2LBh8Pb2hqenJxwcHKClpSXEfPjhhzh16hR69OiBjz/+GNHR0XLfFK1atQopKSmwsrJCjx49niifzZs3w8XFBcOGDYOHhwdkMhkOHDhQZ9k3ERERERFRaxLJGvs6gKgBFRUVsLS0xKpVqxAYGAiJRILg4GC591mTYsrKymBgYICNKZnQ1tFt7XSIiIiIiJ4ZdyvuIHCQC0pLS6Gvr9/a6TwWLi8nhWRnZ+Ps2bNwc3NDaWkplixZAgBczk1ERERERNQIFt2ksJUrVyI/P194fP7Ro0cbfK0XERERERERsegmBfXo0QOZmZkNHi8oKHh6yRARERERET0n+CA1IiIiIiIiIiVh0U1ERERERESkJHx6OVEre/j08uf5iYxERERERMrwIvyuzJluIiIiIiIiIiVh0U1ERERERESkJCy6iYiIiIiIiJSERTcRERERERGRkrDoJiIiIiIiIlIStdZOgIge2HIkD2Id3dZOg4iIiIjomXGv4k5rp/DEONNNREREREREpCQsuomIiIiIiIiUhEU3ERERERERkZKw6CYiIiIiIiJSEhbdRERERERERErCopuoEQUFBRCJRMjJyVG4z6JFi+Ds7Ky0nIiIiIiISN6RI0cwfPhwWFhYQCQSYd++fU32OXToEHr27AlNTU3Y2dkhPj6+TkxcXBwkEgm0tLTg7u6OkydPNjs3Ft303Ll16xZee+01WFhYQFNTE1ZWVggKCkJZWVmLn8vKygpFRUXo2rWrwn3mzJmD1NTUFs+FiIiIiIjqV1FRAScnJ8TFxSkUf+nSJQwdOhT9+/dHTk4OgoODMXnyZCQnJwsxu3btQkhICCIiIpCVlQUnJyf4+Pjg+vXrzcpNJJPJZM3qQdTK/vnnH+zcuRO9evWCsbExzp8/jxkzZqBnz57YsWNHa6fXbGVlZTAwMMBnPxzne7qJiIiIiB5xr+IOZg3/D0pLS6Gvr69QH5FIhO+++w5+fn4Nxnz00UdITEzEmTNnhLaxY8fi9u3bSEpKAgC4u7ujV69eiI2NBQBIpVJYWVlh5syZCAsLU/gaONNNz6TKykrMmjULJiYm0NLSQp8+fZCRkQEAaNOmDaZNmwZXV1d06NABAwcOxPTp03H06NFGx5w4cSL8/PywfPlymJqawtDQEEuWLEFNTQ3mzp0LIyMjtG/fHps3bxb6/Ht5+aFDhyASiZCamgpXV1doa2ujd+/eyM/PF/pweTkRERER0bMtPT0d3t7ecm0+Pj5IT08HAFRVVSEzM1MuRkVFBd7e3kKMolh00zMpNDQUe/bswZYtW5CVlQU7Ozv4+Pjg77//rhN77do17N27F/369Wty3IMHD+LatWs4cuQIoqOjERERgWHDhqFNmzY4ceIEpk6divfffx9//fVXo+PMmzcPq1atwqlTp6CmpoZJkyY99rUSEREREdHTVVxcDFNTU7k2U1NTlJWV4d69e7h58yZqa2vrjSkuLm7WuVh00zOnoqIC69atw4oVK+Dr6wtHR0esX78eYrEYGzduFOLGjRsHbW1tWFpaQl9fHxs2bGhybCMjI3z22Wewt7fHpEmTYG9vj7t37+K///0vOnXqhPDwcGhoaODYsWONjrNs2TL069cPjo6OCAsLw6+//or79+8rdH2VlZUoKyuT24iIiIiI6MXEopueORcuXEB1dTU8PT2FNnV1dbi5uSEvL09oW716NbKysvD999/jwoULCAkJAQAUFhZCV1dX2JYvXy706dKlC1RU/u+fvampKbp16ybsq6qqom3btk0+HKF79+7Cn83NzQFA4QcqREZGwsDAQNisrKwU6kdERERERC3DzMwMJSUlcm0lJSXQ19eHWCxGu3btoKqqWm+MmZlZs86l9sTZErUSMzMzmJmZoXPnzjAyMsKrr76KBQsWwMLCQu4VX0ZGRsKf1dXV5cYQiUT1tkml0kbP/WgfkUgEAE32eSg8PFz4ggB48CA1Ft5ERERERE+Ph4cHDhw4INeWkpICDw8PAICGhgZcXFyQmpoqPJBNKpUiNTUVQUFBzToXi2565tja2kJDQwNpaWno0KEDAKC6uhoZGRkIDg6ut8/DgreyshJqamqws7N7Wuk2m6amJjQ1NVs7DSIiIiKiF8adO3dw/vx5Yf/SpUvIycmBkZERrK2tER4ejqtXr2Lr1q0AgKlTpyI2NhahoaGYNGkSDh48iG+++QaJiYnCGCEhIfD394erqyvc3NwQExODiooKBAQENCs3Ft30zNHR0cG0adOEJ4pbW1sjKioKd+/eRWBgIA4cOICSkhL06tULurq6+OOPPzB37lx4enpCIpG0dvpERERERPSUnTp1Cv379xf2H64s9ff3R3x8PIqKilBYWCgc79ixIxITEzF79mysWbMG7du3x4YNG+Dj4yPEjBkzBjdu3MDChQtRXFwMZ2dnJCUl1Xm4WlNYdNMz6ZNPPoFUKsW7776L8vJyuLq6Ijk5GW3atIFYLMb69esxe/ZsVFZWwsrKCm+88Uaz3pVHREREREQvDi8vL8hksgaPx8fH19snOzu70XGDgoKavZz830SyxjIjIqUrKyuDgYEBPvvhOMQ6uq2dDhERERHRM+NexR3MGv4flJaWQl9fv7XTeSx8ejkRERERERGRkrDoJiIiIiIiIlISFt1ERERERERESsKim4iIiIiIiEhJWHQTERERERERKQmLbiIiIiIiIiIl4SvDiFrZw1eGPc+vQSAiIiIiUoYX4XdlznQTERERERERKQmLbiIiIiIiIiIlYdFNREREREREpCQsuomIiIiIiIiUhEU3ERERERERkZKotXYCRPTAupTfoaWt29ppEBERERE9M+7fvdPaKTwxznQTERERERERKQmLbiIiIiIiIiIlYdFNREREREREpCQsuomIiIiIiIiUhEU3ERERERERkZKw6CZqhEQiQUxMTGunQUREREREjThy5AiGDx8OCwsLiEQi7Nu3r8k+hw4dQs+ePaGpqQk7OzvEx8fXiYmLi4NEIoGWlhbc3d1x8uTJZufGopsem6L/mPfu3QtXV1cYGhpCR0cHzs7OSEhIaLTPoUOHIBKJ6mzFxcWN9mORTERERET08qmoqICTkxPi4uIUir906RKGDh2K/v37IycnB8HBwZg8eTKSk5OFmF27diEkJAQRERHIysqCk5MTfHx8cP369Wblxvd0k9IZGRlh3rx56Ny5MzQ0NPDjjz8iICAAJiYm8PHxabRvfn4+9PX1hX0TExNlpwsAqKqqgoaGxlM5FxERERERPRlfX1/4+voqHP/FF1+gY8eOWLVqFQDAwcEBx44dw+rVq4UaJTo6GlOmTEFAQIDQJzExEZs2bUJYWJjC5+JM90uqvLwc48ePh46ODszNzbF69Wp4eXkhODgYwIMZ46VLl2LcuHHQ0dGBpaWl3LdGEokEADBy5EiIRCJhvz5eXl4YOXIkHBwcYGtriw8++ADdu3fHsWPHmszTxMQEZmZmwqai0vA/WS8vL1y+fBmzZ88WZsYBYNGiRXB2dpaLjYmJkct54sSJ8PPzw7Jly2BhYQF7e3u5z6qhzwEACgsLMWLECOjq6kJfXx+jR49GSUlJk9dGREREREStIz09Hd7e3nJtPj4+SE9PB/BgEi4zM1MuRkVFBd7e3kKMolh0v6RCQkKQlpaG/fv3IyUlBUePHkVWVpZczIoVK+Dk5ITs7GyEhYXhgw8+QEpKCgAgIyMDALB582YUFRUJ+02RyWRITU1Ffn4++vbt22S8s7MzzM3NMWjQIKSlpTUau3fvXrRv3x5LlixBUVERioqKFMrpoYd5paSk4McffxTaG/scpFIpRowYgb///huHDx9GSkoKLl68iDFjxjTr3ERERERE9PQUFxfD1NRUrs3U1BRlZWW4d+8ebt68idra2npjmrrl9d+4vPwlVF5eji1btmDHjh0YOHAggAfFs4WFhVycp6ensGzilVdeQVpaGlavXo1BgwbB2NgYAGBoaAgzM7Mmz1laWgpLS0tUVlZCVVUVn3/+OQYNGtRgvLm5Ob744gu4urqisrISGzZsgJeXF06cOIGePXvW28fIyAiqqqrQ09NTKKd/09HRwYYNG+osK2/sc0hNTcXp06dx6dIlWFlZAQC2bt2KLl26ICMjA7169apznsrKSlRWVgr7ZWVlzc6ViIiIiIieD5zpfgldvHgR1dXVcHNzE9oMDAzkllQDgIeHR539vLy8BsctLCyErq6usC1fvlw4pqenh5ycHGRkZGDZsmUICQnBoUOHGhzL3t4e77//PlxcXNC7d29s2rQJvXv3xurVqwEA27dvlzvX0aNHm/MR1Ktbt2713sfd2OeQl5cHKysroeAGAEdHRxgaGjb4WUVGRsLAwEDYHu1LRERERETKZ2ZmVueW0JKSEujr60MsFqNdu3ZQVVWtN6a5E3yc6aYWY2FhgZycHGHfyMhI+LOKigrs7OwAPFgynpeXh8jISHh5eSk8vpubm3Af+Ouvvw53d3fhmKWlZYP9VFRUIJPJ5Nqqq6vrxOno6Cicy5MIDw9HSEiIsF9WVsbCm4iIiIjoKfLw8MCBAwfk2lJSUoQJNw0NDbi4uCA1NRV+fn4AHtxampqaiqCgoGadi0X3S8jGxgbq6urIyMiAtbU1gAfLv//880+5+6yPHz8u1+/48eNwcHAQ9tXV1VFbWyvsq6mpCYV1U6RSqdwSa0Xk5OTA3NwcwIOZcz09vToxGhoacjkBgLGxMYqLiyGTyYSHqz365UBTGvscHBwccOXKFVy5ckUonHNzc3H79m04OjrWO56mpiY0NTUVPj8RERERETXuzp07OH/+vLB/6dIl5OTkwMjICNbW1ggPD8fVq1exdetWAMDUqVMRGxuL0NBQTJo0CQcPHsQ333yDxMREYYyQkBD4+/vD1dUVbm5uiImJQUVFhfA0c0Wx6H4J6enpwd/fH3PnzoWRkRFMTEwQEREBFRUVoSgFgLS0NERFRcHPzw8pKSnYvXu33D9CiUSC1NRUeHp6QlNTE23atKn3fJGRkXB1dYWtrS0qKytx4MABJCQkYN26dULMv38IYmJi0LFjR3Tp0gX379/Hhg0bcPDgQfz888+NXptEIsGRI0cwduxYaGpqol27dvDy8sKNGzcQFRWFN998E0lJSfjpp5/kXkXWmMY+B29vb3Tr1g3jx49HTEwMampqMH36dPTr1w+urq4KjU9ERERERE/m1KlT6N+/v7D/cGWpv78/4uPjUVRUhMLCQuF4x44dkZiYiNmzZ2PNmjVo3749NmzYIPdK4zFjxuDGjRtYuHAhiouL4ezsjKSkpDoPV2sKi+6XVHR0NKZOnYphw4ZBX18foaGhuHLlCrS0tISYDz/8EKdOncLixYuhr6+P6OhouX+Eq1atQkhICNavXw9LS0sUFBTUe66KigpMnz4df/31F8RiMTp37oxt27bJPeH73z8EVVVV+PDDD3H16lVoa2uje/fu+N///if3g1SfJUuW4P333xcKfJlMBgcHB3z++edYvnw5li5dilGjRmHOnDn46quvFPqsGvscRCIRvv/+e8ycORN9+/aFiooKXnvtNaxdu1ahsYmIiIiI6Ml5eXnVuaX0UfHx8fX2yc7ObnTcoKCgZi8n/zeRrLHM6KVRUVEBS0tLrFq1CoGBgZBIJAgODhbe203KU1ZWBgMDA3zy7VFoaeu2djpERERERM+M+3fvIOzNV1FaWqrwStVnDWe6X1LZ2dk4e/Ys3NzcUFpaiiVLlgAARowY0cqZERERERERvThYdL/EVq5cifz8fOHJfEePHkW7du1aOy0iIiIiIqIXBovul1SPHj2QmZnZ4PGG7s8mIiIiIiIixam0dgJERERERERELyoW3URERERERERKwqeXE7Wyh08vf56fyEhEREREpAwvwu/KnOkmIiIiIiIiUhIW3URERERERERKwqKbiIiIiIiISElYdBMREREREREpCYtuIiIiIiIiIiVRa+0EiOiBFT9kQktbt7XTICIiIiJ6Zty/e6e1U3hinOkmIiIiIiIiUhIW3URERERERERKwqKbiIiIiIiISElYdBMREREREREpCYtuIiIiIiIiIiVh0U1ERERERETPtSNHjmD48OGwsLCASCTCvn37muxz6NAh9OzZE5qamrCzs0N8fHydmLi4OEgkEmhpacHd3R0nT55sdm4suqlVSSQSxMTEtHYaRERERET0HKuoqICTkxPi4uIUir906RKGDh2K/v37IycnB8HBwZg8eTKSk5OFmF27diEkJAQRERHIysqCk5MTfHx8cP369WblxqL7GaboNzR79+6Fq6srDA0NoaOjA2dnZyQkJDTa59ChQxCJRHW24uLiRvs9T0Xy77//jldffRVaWlqwsrJCVFSU3PE//vgDo0aNgkQigUgkqve6IiMj0atXL+jp6cHExAR+fn7Iz8+Xi/Hy8qrzOU6dOlWZl0ZERERERI/w9fXFxx9/jJEjRyoU/8UXX6Bjx45YtWoVHBwcEBQUhDfffBOrV68WYqKjozFlyhQEBATA0dERX3zxBbS1tbFp06Zm5cai+wVgZGSEefPmIT09Hb///jsCAgIQEBAg9y1NQ/Lz81FUVCRsJiYmTyFjoKqqSqnjl5WVYfDgwejQoQMyMzOxYsUKLFq0CF999ZUQc/fuXdjY2OCTTz6BmZlZveMcPnwYM2bMwPHjx5GSkoLq6moMHjwYFRUVcnFTpkyR+xz/XeATEREREdGzIz09Hd7e3nJtPj4+SE9PB/CgXsnMzJSLUVFRgbe3txCjKBbdSlJeXo7x48dDR0cH5ubmWL16Nby8vBAcHAzgwYzx0qVLMW7cOOjo6MDS0lJuKYREIgEAjBw5EiKRSNivj5eXF0aOHAkHBwfY2trigw8+QPfu3XHs2LEm8zQxMYGZmZmwqag0/E/Cy8sLly9fxuzZs4UZXQBYtGgRnJ2d5WJjYmLkcp44cSL8/PywbNkyWFhYwN7eXu6zauhzAIDCwkKMGDECurq60NfXx+jRo1FSUtLodW3fvh1VVVXYtGkTunTpgrFjx2LWrFmIjo4WYnr16oUVK1Zg7Nix0NTUrHecpKQkTJw4EV26dIGTkxPi4+NRWFiIzMxMuThtbW25z1FfX7/R/IiIiIiIqPUUFxfD1NRUrs3U1BRlZWW4d+8ebt68idra2npjmlod/G8supUkJCQEaWlp2L9/P1JSUnD06FFkZWXJxaxYsQJOTk7Izs5GWFgYPvjgA6SkpAAAMjIyAACbN29GUVGRsN8UmUyG1NRU5Ofno2/fvk3GOzs7w9zcHIMGDUJaWlqjsXv37kX79u2xZMkSYUa3OR7mlZKSgh9//FFob+xzkEqlGDFiBP7++28cPnwYKSkpuHjxIsaMGdPoudLT09G3b19oaGgIbT4+PsjPz8c///zTrLwfVVpaCuDB6oJHbd++He3atUPXrl0RHh6Ou3fvNjhGZWUlysrK5DYiIiIiInoxqbV2Ai+i8vJybNmyBTt27MDAgQMBPCieLSws5OI8PT0RFhYGAHjllVeQlpaG1atXY9CgQTA2NgYAGBoaNrj0+VGlpaWwtLREZWUlVFVV8fnnn2PQoEENxpubm+OLL76Aq6srKisrsWHDBnh5eeHEiRPo2bNnvX2MjIygqqoKPT09hXL6Nx0dHWzYsEGuEAYa/xxSU1Nx+vRpXLp0CVZWVgCArVu3okuXLsjIyECvXr3qPVdxcTE6duwo1/bwW6ri4mK0adOm2flLpVIEBwfD09MTXbt2FdrffvttdOjQARYWFvj999/x0UcfIT8/H3v37q13nMjISCxevLjZ5yciIiIiopZhZmZWZ/VsSUkJ9PX1IRaLoaqqClVV1XpjmlsLcaZbCS5evIjq6mq4ubkJbQYGBnJLqgHAw8Ojzn5eXl6D4xYWFkJXV1fYli9fLhzT09NDTk4OMjIysGzZMoSEhODQoUMNjmVvb4/3338fLi4u6N27NzZt2oTevXsLDw7Yvn273LmOHj3anI+gXt26datTcAONfw55eXmwsrISCm4AcHR0hKGhoRDTpUsXIU9fX98nzrMhM2bMwJkzZ7Bz50659vfeew8+Pj7o1q0bxo8fj61bt+K7777DhQsX6h0nPDwcpaWlwnblyhWl5UxERERERHV5eHggNTVVri0lJUWoTTQ0NODi4iIXI5VKkZqaWqd+aQpnup8jFhYWyMnJEfYfXeKsoqICOzs7AA+WjOfl5SEyMhJeXl4Kj+/m5ibcB/7666/D3d1dOGZpadlgPxUVFchkMrm26urqOnE6OjoK59IcBw4cEM4nFosBNPzN1cNjzRUUFIQff/wRR44cQfv27RuNffi5nT9/Hra2tnWOa2pqNngPORERERERNd+dO3dw/vx5Yf/SpUvIycmBkZERrK2tER4ejqtXr2Lr1q0AgKlTpyI2NhahoaGYNGkSDh48iG+++QaJiYnCGCEhIfD394erqyvc3NwQExODiooKBAQENCs3Ft1KYGNjA3V1dWRkZMDa2hrAg+Xff/75p9x91sePH5frd/z4cTg4OAj76urqqK2tFfbV1NSEwropUqkUlZWVzco7JycH5ubmAB7MnOvp6dWJ0dDQkMsJAIyNjVFcXAyZTCY8XO3RLwea0tjn4ODggCtXruDKlSvCbHdubi5u374NR0dHAECHDh3qjOnh4YF58+ahuroa6urqAB58c2Vvb9+speUymQwzZ87Ed999h0OHDtVZsl6fh9f+8LMkIiIiIiLlOnXqFPr37y/sh4SEAAD8/f0RHx+PoqIiFBYWCsc7duyIxMREzJ49G2vWrEH79u2xYcMG+Pj4CDFjxozBjRs3sHDhQhQXF8PZ2RlJSUl1Hq7WFBbdSqCnpwd/f3/MnTsXRkZGMDExQUREBFRUVISiFADS0tIQFRUFPz8/pKSkYPfu3XLfrEgkEqSmpsLT0xOampoNFouRkZFwdXWFra0tKisrceDAASQkJGDdunVCzL+/2YmJiUHHjh3RpUsX3L9/Hxs2bMDBgwfx888/N3ptEokER44cEZ743a5dO3h5eeHGjRuIiorCm2++iaSkJPz0008KP8G7sc/B29tbWLYdExODmpoaTJ8+Hf369YOrq2uDY7799ttYvHgxAgMD8dFHH+HMmTNYs2aN3Hv3qqqqkJubK/z56tWryMnJga6urvDlxowZM7Bjxw58//330NPTE55UaGBgALFYjAsXLmDHjh0YMmQI2rZti99//x2zZ89G37590b17d4Wun4iIiIiInoyXl1ed1bePio+Pr7dPdnZ2o+MGBQUhKCjoiXLjPd1KEh0dDQ8PDwwbNgze3t7w9PSEg4MDtLS0hJgPP/wQp06dQo8ePfDxxx8jOjpa7puVVatWISUlBVZWVujRo0eD56qoqMD06dPRpUsXeHp6Ys+ePdi2bRsmT54sxPz7m52qqip8+OGH6NatG/r164fffvsN//vf/4QHvzVkyZIlKCgogK2trfCwNwcHB3z++eeIi4uDk5MTTp48iTlz5ij8WTX2OYhEInz//fdo06YN+vbtC29vb9jY2GDXrl2NjmlgYICff/4Zly5dgouLCz788EMsXLgQ7733nhBz7do19OjRAz169EBRURFWrlyJHj16yH1u69atQ2lpKby8vGBubi5sD8+voaGB//3vfxg8eDA6d+6MDz/8EKNGjcIPP/yg8PUTEREREdGLSyRr7OsAajEVFRWwtLTEqlWrEBgYCIlEguDgYOG93fTyKisrg4GBAeZvOwgtbd3WToeIiIiI6Jlx/+4dfPzOAJSWliq8kvZZw+XlSpKdnY2zZ8/Czc0NpaWlWLJkCQBgxIgRrZwZERERERERPS0supVo5cqVyM/PFx43f/ToUbRr16610yIiIiIiIqKnhEW3kvTo0QOZmZkNHi8oKHh6yRAREREREVGr4IPUiIiIiIiIiJSERTcRERERERGRkvDp5USt7OHTy5/nJzISERERESnDi/C7Mme6iYiIiIiIiJSERTcRERERERGRkrDoJiIiIiIiIlISFt1ERERERERESsKim4iIiIiIiEhJ1Fo7ASJ6IOKb49DU1mntNIiIiIiInhmVdytaO4UnxpluIiIiIiIiIiVh0U1ERERERESkJCy6iYiIiIiIiJSERTcRERERERGRkrDoJiIiIiIiIlISFt1ERERERET0XDty5AiGDx8OCwsLiEQi7Nu3r8k+hw4dQs+ePaGpqQk7OzvEx8fXiYmLi4NEIoGWlhbc3d1x8uTJZufGopvoCdy6dQuvvfYaLCwsoKmpCSsrKwQFBaGsrKy1UyMiIiIiemlUVFTAyckJcXFxCsVfunQJQ4cORf/+/ZGTk4Pg4GBMnjwZycnJQsyuXbsQEhKCiIgIZGVlwcnJCT4+Prh+/XqzchPJZDJZs3oQkeCff/7Bzp070atXLxgbG+P8+fOYMWMGevbsiR07dig0RllZGQwMDBC8Ppnv6SYiIiIiekTl3QrETPFBaWkp9PX1FeojEonw3Xffwc/Pr8GYjz76CImJiThz5ozQNnbsWNy+fRtJSUkAAHd3d/Tq1QuxsbEAAKlUCisrK8ycORNhYWEKXwNnuomaUFlZiVmzZsHExARaWlro06cPMjIyAABt2rTBtGnT4Orqig4dOmDgwIGYPn06jh492spZExERERFRQ9LT0+Ht7S3X5uPjg/T0dABAVVUVMjMz5WJUVFTg7e0txCiKRTdRE0JDQ7Fnzx5s2bIFWVlZsLOzg4+PD/7+++86sdeuXcPevXvRr1+/VsiUiIiIiIgUUVxcDFNTU7k2U1NTlJWV4d69e7h58yZqa2vrjSkuLm7WuVh0EzWioqIC69atw4oVK+Dr6wtHR0esX78eYrEYGzduFOLGjRsHbW1tWFpaQl9fHxs2bGhwzMrKSpSVlcltRERERET0YmLRTdSICxcuoLq6Gp6enkKburo63NzckJeXJ7StXr0aWVlZ+P7773HhwgWEhIQ0OGZkZCQMDAyEzcrKSqnXQERERERE8szMzFBSUiLXVlJSAn19fYjFYrRr1w6qqqr1xpiZmTXrXCy6iVqAmZkZOnfujNdffx1ffvkl1q1bh6Kionpjw8PDUVpaKmxXrlx5ytkSEREREb3cPDw8kJqaKteWkpICDw8PAICGhgZcXFzkYqRSKVJTU4UYRbHoJmqEra0tNDQ0kJaWJrRVV1cjIyMDjo6O9faRSqUAHiwjr4+mpib09fXlNiIiIiIienx37txBTk4OcnJyADx4JVhOTg4KCwsBPJj4mjBhghA/depUXLx4EaGhoTh79iw+//xzfPPNN5g9e7YQExISgvXr12PLli3Iy8vDtGnTUFFRgYCAgGblpvbkl0f04tLR0cG0adMwd+5cGBkZwdraGlFRUbh79y4CAwNx4MABlJSUoFevXtDV1cUff/yBuXPnwtPTExKJpLXTJyIiIiJ6KZw6dQr9+/cX9h/e7unv74/4+HgUFRUJBTgAdOzYEYmJiZg9ezbWrFmD9u3bY8OGDfDx8RFixowZgxs3bmDhwoUoLi6Gs7MzkpKS6jxcrSl8TzdRE+7fv4/Q0FB8/fXXKC8vh6urK1avXo1evXrhl19+wbx585Cbm4vKykpYWVnhjTfeQFhYGAwNDRUan+/pJiIiIiKq3+O8p/tZw6KbqJWx6CYiIiIiqt+LUHTznm4iIiIiIiIiJWHRTURERERERKQkLLqJiIiIiIiIlIRFNxEREREREZGSsOgmIiIiIiIiUhIW3URERERERERKwleGEbWyh68Me55fg0BEREREpAwvwu/KnOkmIiIiIiIiUhIW3URERERERERKwqKbiIiIiIiISElYdBMREREREREpCYtuIiIiIiIiIiVRa+0EiOiBuQlHoSHWae00iIiIiIieGVX3Klo7hSfGmW4iIiIiIiIiJWHRTURERERERKQkLLqJiIiIiIiIlIRFNxEREREREZGSsOgmIiIiIiIiUhIW3USNKCgogEgkQk5OjsJ9Fi1aBGdnZ6XlRERERERE8o4cOYLhw4fDwsICIpEI+/bta7LPoUOH0LNnT2hqasLOzg7x8fF1YuLi4iCRSKClpQV3d3ecPHmy2bmx6Kbn2q1bt9C+fXuIRCLcvn27xce3srJCUVERunbtqnCfOXPmIDU1tcVzISIiIiKi+lVUVMDJyQlxcXEKxV+6dAlDhw5F//79kZOTg+DgYEyePBnJyclCzK5duxASEoKIiAhkZWXByckJPj4+uH79erNyE8lkMlmzehA9Q/z8/FBVVYWffvoJ//zzDwwNDVs7pWYrKyuDgYEB3ov9ke/pJiIiIiJ6RNW9CnwVNAylpaXQ19dXqI9IJMJ3330HPz+/BmM++ugjJCYm4syZM0Lb2LFjcfv2bSQlJQEA3N3d0atXL8TGxgIApFIprKysMHPmTISFhSl8DZzppmdSZWUlZs2aBRMTE2hpaaFPnz7IyMiQi1m3bh1u376NOXPmKDTmxIkT4efnh+XLl8PU1BSGhoZYsmQJampqMHfuXBgZGaF9+/bYvHmz0Offy8sPHToEkUiE1NRUuLq6QltbG71790Z+fr7Qh8vLiYiIiIiebenp6fD29pZr8/HxQXp6OgCgqqoKmZmZcjEqKirw9vYWYhTFopueSaGhodizZw+2bNmCrKws2NnZwcfHB3///TcAIDc3F0uWLMHWrVuhoqL4P+ODBw/i2rVrOHLkCKKjoxEREYFhw4ahTZs2OHHiBKZOnYr3338ff/31V6PjzJs3D6tWrcKpU6egpqaGSZMmPdH1EhERERHR01NcXAxTU1O5NlNTU5SVleHevXu4efMmamtr640pLi5u1rlYdNMzp6KiAuvWrcOKFSvg6+sLR0dHrF+/HmKxGBs3bkRlZSXGjRuHFStWwNraulljGxkZ4bPPPoO9vT0mTZoEe3t73L17F//973/RqVMnhIeHQ0NDA8eOHWt0nGXLlqFfv35wdHREWFgYfv31V9y/f1+hHCorK1FWVia3ERERERHRi4lFNz1zLly4gOrqanh6egpt6urqcHNzQ15eHsLDw+Hg4IB33nmn3v6FhYXQ1dUVtuXLlwvHunTpIjczbmpqim7dugn7qqqqaNu2bZMPR+jevbvwZ3NzcwBQ+IEKkZGRMDAwEDYrKyuF+hERERERUcswMzNDSUmJXFtJSQn09fUhFovRrl07qKqq1htjZmbWrHOx6KbnzsGDB7F7926oqalBTU0NAwcOBAC0a9cOERERsLCwQE5OjrBNnTpV6Kuuri43lkgkqrdNKpU2msOjfUQiEQA02eeh8PBwlJaWCtuVK1cU6kdERERERC3Dw8OjzhuHUlJS4OHhAQDQ0NCAi4uLXIxUKkVqaqoQoyi1J0+XqGXZ2tpCQ0MDaWlp6NChAwCguroaGRkZCA4Oxrx583Dv3j0hPiMjA5MmTcLRo0dha2sLNTU12NnZtVb6TdLU1ISmpmZrp0FERERE9MK4c+cOzp8/L+xfunQJOTk5MDIygrW1NcLDw3H16lVs3boVADB16lTExsYiNDQUkyZNwsGDB/HNN98gMTFRGCMkJAT+/v5wdXWFm5sbYmJiUFFRgYCAgGblxqKbnjk6OjqYNm2a8ERxa2trREVF4e7duwgMDESbNm3k4m/evAkAcHBweC5fGUZERERERE/m1KlT6N+/v7AfEhICAPD390d8fDyKiopQWFgoHO/YsSMSExMxe/ZsrFmzBu3bt8eGDRvg4+MjxIwZMwY3btzAwoULUVxcDGdnZyQlJdV5uFpTWHTTM+mTTz6BVCrFu+++i/Lycri6uiI5OblOwU1EREREROTl5QWZTNbg8fj4+Hr7ZGdnNzpuUFAQgoKCnig3kayxzIhI6crKymBgYID3Yn+EhlintdMhIiIiInpmVN2rwFdBw1BaWgp9ff3WTuex8EFqRERERERERErCopuIiIiIiIhISVh0ExERERERESkJi24iIiIiIiIiJWHRTURERERERKQkfHo5USt7+PTy5/mJjEREREREyvAi/K7MmW4iIiIiIiIiJWHRTURERERERKQkLLqJiIiIiIiIlIRFNxEREREREZGSsOgmIiIiIiIiUhK11k6AiB6Ytv4gNMQ6rZ0GEREREdFTt3n6oNZOQWk4001ERERERESkJCy6iYiIiIiIiJSERTcRERERERGRkrDoJiIiIiIiIlISFt1ERERERERESsKim4iIiIiIiJ4LcXFxkEgk0NLSgru7O06ePNlgbHV1NZYsWQJbW1toaWnByckJSUlJcjHl5eUIDg5Ghw4dIBaL0bt3b2RkZLRoziy6iYiIiIiI6Jm3a9cuhISEICIiAllZWXBycoKPjw+uX79eb/z8+fPx5ZdfYu3atcjNzcXUqVMxcuRIZGdnCzGTJ09GSkoKEhIScPr0aQwePBje3t64evVqi+XNopteSiKRCPv27WtWn507d0IkEsHPz08pORERERERUcOio6MxZcoUBAQEwNHREV988QW0tbWxadOmeuMTEhLw3//+F0OGDIGNjQ2mTZuGIUOGYNWqVQCAe/fuYc+ePYiKikLfvn1hZ2eHRYsWwc7ODuvWrWuxvFl0EymgoKAAc+bMwauvvtraqRARERERvXSqqqqQmZkJb29voU1FRQXe3t5IT0+vt09lZSW0tLTk2sRiMY4dOwYAqKmpQW1tbaMxLYFFNz13ysvLMX78eOjo6MDc3ByrV6+Gl5cXgoODAQASiQRLly7FuHHjoKOjA0tLS8TFxQn9JRIJAGDkyJEQiUTCfkNqa2sxfvx4LF68GDY2NnWO//PPP5gwYQLatGkDbW1t+Pr64ty5cy11uUREREREL71bt26htrYWpqamcu2mpqYoLi6ut4+Pjw+io6Nx7tw5SKVSpKSkYO/evSgqKgIA6OnpwcPDA0uXLsW1a9dQW1uLbdu2IT09XYhpCSy66bkTEhKCtLQ07N+/HykpKTh69CiysrLkYlasWAEnJydkZ2cjLCwMH3zwAVJSUgBAeDDC5s2bUVRU1OSDEpYsWQITExMEBgbWe3zixIk4deoU9u/fj/T0dMhkMgwZMgTV1dX1xldWVqKsrExuIyIiIiKilrVmzRp06tQJnTt3hoaGBoKCghAQEAAVlf8rgxMSEiCTyWBpaQlNTU189tlnGDdunFzMk1JrsZGInoLy8nJs2bIFO3bswMCBAwE8KJ4tLCzk4jw9PREWFgYAeOWVV5CWlobVq1dj0KBBMDY2BgAYGhrCzMys0fMdO3YMGzduRE5OTr3Hz507h/379yMtLQ29e/cGAGzfvh1WVlbYt28f3nrrrTp9IiMjsXjx4mZdNxERERHRy6xt27ZQVVVFSUmJXHtJSUmDv9MbGxtj3759uH//Pm7dugULCwuEhYXJrV61tbXF4cOHUVFRgbKyMpibm2PMmDH1rnB9XJzppufKxYsXUV1dDTc3N6HNwMAA9vb2cnEeHh519vPy8hoct7CwELq6usK2fPlylJeX491338X69evRrl27evvl5eVBTU0N7u7uQlvbtm1hb2/f4PnCw8NRWloqbFeuXGnyuomIiIiIXmYaGhpwcXFBamqq0CaVSpGamlrnd/9/09LSgqWlJWpqarBnzx6MGDGiTszDW1f/+ecfJCcn1xvzuDjTTQTAwsJCbjbbyMgIFy5cQEFBAYYPHy60S6VSAICamhry8/Mf61yamprQ1NR8onyJiIiIiF42ISEh8Pf3h6urK9zc3BATE4OKigoEBAQAACZMmABLS0tERkYCAE6cOIGrV6/C2dkZV69exaJFiyCVShEaGiqMmZycDJlMBnt7e5w/fx5z585F586dhTFbAotueq7Y2NhAXV0dGRkZsLa2BgCUlpbizz//RN++fYW448ePy/U7fvw4HBwchH11dXXU1tYK+2pqarCzs5Pro62tjdOnT8u1zZ8/H+Xl5VizZg2srKwglUpRU1ODEydOCMvLb926hfz8fDg6OrbMRRMREREREcaMGYMbN25g4cKFKC4uhrOzM5KSkoSHqxUWFsrdi33//n3Mnz8fFy9ehK6uLoYMGYKEhAQYGhoKMaWlpQgPD8dff/0FIyMjjBo1CsuWLYO6unqL5c2im54renp68Pf3x9y5c2FkZAQTExNERERARUUFIpFIiEtLS0NUVBT8/PyQkpKC3bt3IzExUTgukUiQmpoKT09PaGpqok2bNnXOpaWlha5du8q1PfwBfdjeqVMnjBgxAlOmTMGXX34JPT09hIWFwdLSskWXpBARERERERAUFISgoKB6jx06dEhuv1+/fsjNzW10vNGjR2P06NEtlV69eE83PXeio6Ph4eGBYcOGwdvbG56ennBwcJB7v96HH36IU6dOoUePHvj4448RHR0NHx8f4fiqVauQkpICKysr9OjR44ny2bx5M1xcXDBs2DB4eHhAJpPhwIEDLfrtGBERERERPZ9EMplM1tpJED2JiooKWFpaYtWqVQgMDIREIkFwcLDw3u5nXVlZGQwMDPD2yu+gIdZp7XSIiIiIiJ66zdMH1dv+8Hfl0tJS6OvrP+WsWgaXl9NzJzs7G2fPnoWbmxtKS0uxZMkSAOBybiIiIiIieuaw6Kbn0sqVK5Gfny+8OuDo0aMNvtaLiIiIiIiotbDopudOjx49kJmZ2eDxgoKCp5cMERERERFRI/ggNSIiIiIiIiIlYdFNREREREREpCRcXk70jFg3ZcBz+0RGIiIiIiKqH2e6iYiIiIiIiJSERTcRERERERGRkrDoJiIiIiIiIlISFt1ERERERERESsKim4iIiIiIiEhJ+PRyomfEhNifoa6l3dppEBERERE9dbtDhrR2CkrDmW4iIiIiIiIiJWHRTURERERERKQkLLqJiIiIiIiIlIRFNxEREREREZGSsOgmIiIiIiIiUhIW3URERERERPRciIuLg0QigZaWFtzd3XHy5MkGY6urq7FkyRLY2tpCS0sLTk5OSEpKkospLy9HcHAwOnToALFYjN69eyMjI6NFc2bRTfSEZs2aBRcXF2hqasLZ2bm10yEiIiIieiHt2rULISEhiIiIQFZWFpycnODj44Pr16/XGz9//nx8+eWXWLt2LXJzczF16lSMHDkS2dnZQszkyZORkpKChIQEnD59GoMHD4a3tzeuXr3aYnmLZDKZrMVGI3oJzZo1C/b29jhx4gR+//135OTkNKt/WVkZDAwMMGLZbr6nm4iIiIheSg29p/vh78qlpaUYNGgQevXqhdjYWACAVCqFlZUVZs6cibCwsDp9LSwsMG/ePMyYMUNoGzVqFMRiMbZt24Z79+5BT08P33//PYYOHSrEuLi4wNfXFx9//HGLXBtnuomaUFlZiVmzZsHExARaWlro06eP3JKTzz77DDNmzICNjU0rZklERERE9OKqqqpCZmYmvL29hTYVFRV4e3sjPT293j6VlZXQ0tKSaxOLxTh27BgAoKamBrW1tY3GtAQW3URNCA0NxZ49e7BlyxZkZWXBzs4OPj4++Pvvv1s7NSIiIiKil8KtW7dQW1sLU1NTuXZTU1MUFxfX28fHxwfR0dE4d+4cpFIpUlJSsHfvXhQVFQEA9PT04OHhgaVLl+LatWuora3Ftm3bkJ6eLsS0BBbdRI2oqKjAunXrsGLFCvj6+sLR0RHr16+HWCzGxo0bH2vMyspKlJWVyW1ERERERNSy1qxZg06dOqFz587Q0NBAUFAQAgICoKLyf2VwQkICZDIZLC0toampic8++wzjxo2Ti3lSLLqJGnHhwgVUV1fD09NTaFNXV4ebmxvy8vIea8zIyEgYGBgIm5WVVUulS0RERET0Qmrbti1UVVVRUlIi115SUgIzM7N6+xgbG2Pfvn2oqKjA5cuXcfbsWejq6srdFmpra4vDhw/jzp07uHLlCk6ePInq6uoWvXWURTfRUxYeHo7S0lJhu3LlSmunRERERET0TNPQ0ICLiwtSU1OFNqlUitTUVHh4eDTaV0tLC5aWlqipqcGePXswYsSIOjE6OjowNzfHP//8g+Tk5HpjHpdai41E9AKytbWFhoYG0tLS0KFDBwAP3veXkZGB4ODgxxpTU1MTmpqaLZglEREREdGLLyQkBP7+/nB1dYWbmxtiYmJQUVGBgIAAAMCECRNgaWmJyMhIAMCJEydw9epVODs74+rVq1i0aBGkUilCQ0OFMZOTkyGTyWBvb4/z589j7ty56Ny5szBmS2DRTdQIHR0dTJs2DXPnzoWRkRGsra0RFRWFu3fvIjAwEABw/vx53LlzB8XFxbh3757wyjBHR0doaGi0YvZERERERC+OMWPG4MaNG1i4cCGKi4vh7OyMpKQk4eFqhYWFcvdi379/H/Pnz8fFixehq6uLIUOGICEhAYaGhkJMaWkpwsPD8ddff8HIyAijRo3CsmXLoK6u3mJ58z3dRE24f/8+QkND8fXXX6O8vByurq5YvXo1evXqBQDw8vLC4cOH6/S7dOkSJBJJk+PzPd1ERERE9LJT5D3d+vr6TzmrlsGim6iVsegmIiIiopfdi1x080FqRERERERERErCopuIiIiIiIhISVh0ExERERERESkJi24iIiIiIiIiJWHRTURERERERKQkLLqJiIiIiIiIlERN0cDPPvtM4UFnzZr1WMkQvcy2Bg1+bl+DQERERERE9VP4Pd0dO3ZUbECRCBcvXnyipIheJi/CuweJiIiIiJThRfhdWeGZ7kuXLikzDyIiIiIiIqIXzhPd011VVYX8/HzU1NS0VD5EREREREREL4zHKrrv3r2LwMBAaGtro0uXLigsLAQAzJw5E5988kmLJkhERERERET0vHqsojs8PBy//fYbDh06BC0tLaHd29sbu3btarHkiIiIiIiIiJ5nCt/T/ah9+/Zh165d+M9//gORSCS0d+nSBRcuXGix5IheJqNW/Ag1Le3WToOIiIiI6Kn7aZ5fa6egNI81033jxg2YmJjUaa+oqJArwomIiIiIiIheZo9VdLu6uiIxMVHYf1hob9iwAR4eHi2TGREREREREdFz7rGWly9fvhy+vr7Izc1FTU0N1qxZg9zcXPz66684fPhwS+dIRERERERE9Fx6rJnuPn36ICcnBzU1NejWrRt+/vlnmJiYID09HS4uLi2dIxEREREREdFz6bFmugHA1tYW69evb8lciIiIiIiIiF4oCs90l5WVKbwRERERERERtbS4uDhIJBJoaWnB3d0dJ0+ebDC2uroaS5Ysga2tLbS0tODk5ISkpCS5mPLycgQHB6NDhw4Qi8Xo3bs3MjIyWjRnhYtuQ0NDtGnTRqGN6HknEomwb9++ZvXZuXMnRCIR/Pz8lJITEREREdHLbNeuXQgJCUFERASysrLg5OQEHx8fXL9+vd74+fPn48svv8TatWuRm5uLqVOnYuTIkcjOzhZiJk+ejJSUFCQkJOD06dMYPHgwvL29cfXq1RbLWySTyWSKBD76gLSCggKEhYVh4sSJwtPK09PTsWXLFkRGRsLf37/FEiRqDSKRCN99953CBXRBQQH69OkDGxsbGBkZNatgLysrg4GBAbznb+d7uomIiIjopdTQe7of/q5cWlqKQYMGoVevXoiNjQUASKVSWFlZYebMmQgLC6vT18LCAvPmzcOMGTOEtlGjRkEsFmPbtm24d+8e9PT08P3332Po0KFCjIuLC3x9ffHxxx+3yLUpPNPdr18/Ydu6dSuio6MRGRmJ119/Ha+//joiIyOxcuVKbN68uUUSI3pc5eXlGD9+PHR0dGBubo7Vq1fDy8sLwcHBAACJRIKlS5di3Lhx0NHRgaWlJeLi4oT+EokEADBy5EiIRCJhvyG1tbUYP348Fi9eDBsbGyVdFRERERHRy6uqqgqZmZnw9vYW2lRUVODt7Y309PR6+1RWVkJLS0uuTSwW49ixYwCAmpoa1NbWNhrTEh7r6eXp6elwdXWt0+7q6tromnqipyEkJARpaWnYv38/UlJScPToUWRlZcnFrFixAk5OTsjOzkZYWBg++OADpKSkAIBwD8fmzZtRVFTU5D0dS5YsgYmJCQIDA5VzQUREREREL7lbt26htrYWpqamcu2mpqYoLi6ut4+Pjw+io6Nx7tw5SKVSpKSkYO/evSgqKgIA6OnpwcPDA0uXLsW1a9dQW1uLbdu2IT09XYhpCY9VdFtZWdX75PINGzbAysrqiZMielzl5eXYsmULVq5ciYEDB6Jr167YvHkzamtr5eI8PT0RFhaGV155BTNnzsSbb76J1atXAwCMjY0BPHiOgZmZmbBfn2PHjmHjxo3NepJ/ZWUlHz5IRERERKRka9asQadOndC5c2doaGggKCgIAQEBUFH5vzI4ISEBMpkMlpaW0NTUxGeffYZx48bJxTypxxpp9erVWLt2Lbp164bJkydj8uTJ6N69O9auXSsULkSt4eLFi6iuroabm5vQZmBgAHt7e7m4h88ieHQ/Ly+vwXELCwuhq6srbMuXL0d5eTneffddrF+/Hu3atVM4x8jISBgYGAgbv6giIiIiImpc27ZtoaqqipKSErn2kpISmJmZ1dvH2NgY+/btQ0VFBS5fvoyzZ89CV1dX7pZQW1tbHD58GHfu3MGVK1dw8uRJVFdXt+hto4/1nu4hQ4bg3Llz+Pzzz3H27FkAwPDhwzF16lQWEPRCsrCwQE5OjrBvZGSECxcuoKCgAMOHDxfapVIpAEBNTQ35+fmwtbWtM1Z4eDhCQkKE/bKyMv7cEBERERE1QkNDAy4uLkhNTRUediyVSpGamoqgoKBG+2ppacHS0hLV1dXYs2cPRo8eXSdGR0cHOjo6+Oeff5CcnIyoqKgWy/2xim4AaN++PZYvX95iiRC1BBsbG6irqyMjIwPW1tYAgNLSUvz555/o27evEHf8+HG5fsePH4eDg4Owr66uLrckXU1NDXZ2dnJ9tLW1cfr0abm2+fPno7y8HGvWrGmwkNbU1ISmpubjXSARERER0UsqJCQE/v7+cHV1hZubG2JiYlBRUYGAgAAAwIQJE2BpaYnIyEgAwIkTJ3D16lU4Ozvj6tWrWLRoEaRSKUJDQ4Uxk5OTIZPJYG9vj/Pnz2Pu3Lno3LmzMGZLeOyi+/bt29i4caOwJLdLly6YNGkSDAwMWiw5oubS09ODv78/5s6dCyMjI5iYmCAiIgIqKioQiURCXFpaGqKiouDn54eUlBTs3r0biYmJwnGJRILU1FR4enpCU1Oz3vfPa2lpoWvXrnJthoaGAFCnnYiIiIiInsyYMWNw48YNLFy4EMXFxXB2dkZSUpLwcLXCwkK5e7Hv37+P+fPn4+LFi9DV1cWQIUOQkJAg/M4OPJigCw8Px19//QUjIyOMGjUKy5Ytg7q6eovlrfB7uh916tQp+Pj4QCwWC/fOZmRk4N69e/j555/Rs2fPFkuQqLnKy8sxdepU7Nu3D/r6+ggNDcXOnTsxYMAAREZGQiKRYNKkSThz5gwSExOhr6+P8PBwzJo1Sxjjhx9+QEhICAoKCmBpaYmCggKFzj1x4kTcvn2b7+kmIiIiImoGRd7Tra+v/3STaiGPVXS/+uqrsLOzw/r166Gm9mCyvKamBpMnT8bFixdx5MiRFk+U6HFVVFTA0tISq1atQmBgICQSCYKDg4X3drc2Ft1ERERE9LJ7kYvux1pefurUKbmCG3hwz2toaGi97+8mepqys7Nx9uxZuLm5obS0FEuWLAEAjBgxopUzIyIiIiKil81jvTJMX18fhYWFddqvXLkCPT29J06K6EmtXLkSTk5O8Pb2RkVFBY4ePdqs13oRERERERG1hMea6R4zZgwCAwOxcuVK9O7dG8CDB1PNnTsX48aNa9EEiZqrR48eyMzMbPC4ovdnExERERERPanHKrpXrlwJkUiECRMmoKamBjKZDBoaGpg2bRo++eSTls6RiIiIiIiI6Ln0WEW3hoYG1qxZg8jISFy4cAEAYGtrC21tPgSKiIiIiIiI6KFmFd2TJk1SKG7Tpk2PlQzRy2zP3GHP7RMZiYiIiIiofs0quuPj49GhQwf06NEDj/GmMSIiIiIiIqKXSrOK7mnTpuHrr7/GpUuXEBAQgHfeeQdGRkbKyo2IiIiIiIjoudasV4bFxcWhqKgIoaGh+OGHH2BlZYXRo0cjOTmZM99ERERERERE/yKSPUG1fPnyZcTHx2Pr1q2oqanBH3/8AV1d3ZbMj+iFV1ZWBgMDA5SWlvKebiIiIiKiR7wIvys3a6a7TmcVFYhEIshkMtTW1rZUTkREREREREQvhGa/MqyyshJ79+7Fpk2bcOzYMQwbNgyxsbF47bXXoKLyRDU80Utt5NKvoaYpbu00iIiIiIiUIvnjCa2dQqtoVtE9ffp07Ny5E1ZWVpg0aRK+/vprtGvXTlm5ERERERERET3XmlV0f/HFF7C2toaNjQ0OHz6Mw4cP1xu3d+/eFkmOiIiIiIiI6HnWrKJ7woQJEIlEysqFiIiIiIiI6IXSrKI7Pj5eSWkQERERERERvXj45DMiIiIiIiIiJWHRTURERERERM+MuLg4SCQSaGlpYcCAAY3GVldXY8mSJbC1tYWWlhacnJyQlJQkF1NbW4sFCxagY8eOEIvFsLW1xdKlSyGTyZR5GQIW3USNEIlE2LdvX2unQURERET0Uti1axdCQkIQERGBrKwsdO3aFQBw48aNeuPnz5+PL7/8EmvXrkVubi6mTp2KkSNHIjs7W4j59NNPsW7dOsTGxiIvLw+ffvopoqKisHbt2qdyTSy66al6nCJ2586dEIlE8PPzU8r4RERERET0bIiOjsaUKVMQEBAAR0dHxMTEAAASEhLqjU9ISMB///tfDBkyBDY2Npg2bRqGDBmCVatWCTG//vorRowYgaFDh0IikeDNN9/E4MGDcfLkyadxSSy66dlWUFCAOXPm4NVXX32q562qqnqq5yMiIiIietlVVVUhMzMT3t7eQpuKyoOSNSMjo94+lZWV0NLSkmsTi8U4duyYsN+7d2+kpqbizz//BAD89ttvOHbsGHx9fVv6EurFopsUVl5ejvHjx0NHRwfm5uZYvXo1vLy8EBwcDACQSCRYunQpxo0bBx0dHVhaWiIuLk7oL5FIAAAjR46ESCQS9htSW1uL8ePHY/HixbCxsWkyv4bGnzhxYp1Z8uDgYHh5eQn7Xl5eCAoKQnBwMNq1awcfHx/hWFFREXx9fSEWi2FjY4Nvv/1WbqzTp09jwIABEIvFaNu2Ld577z3cuXOnyXyJiIiIiOj/3Lx5E7W1tTA1Na1zrKSkpN4+Pj4+iI6Oxrlz5yCVSpGSkoK9e/eiqKhIiAkLC8PYsWPRuXNnqKuro0ePHggODsb48eOVdi2PYtFNCgsJCUFaWhr279+PlJQUHD16FFlZWXIxK1asgJOTE7KzsxEWFoYPPvgAKSkpAP7v26nNmzejqKiowW+rHlqyZAlMTEwQGBioUH7NHf/ftmzZAg0NDaSlpeGLL74Q2hcsWIBRo0bht99+w/jx4zF27Fjk5eUBACoqKuDj44M2bdogIyMDu3fvxv/+9z8EBQU1eJ7KykqUlZXJbURERERE1Hxr1qxBp06d0LlzZ2hoaCAoKAgBAQHCDDkAfPPNN9i+fTt27NiBrKwsbNmyBStXrsSWLVueSo7Nek83vbzKy8uxZcsW7NixAwMHDgTwoLi1sLCQi/P09ERYWBgA4JVXXkFaWhpWr16NQYMGwdjYGABgaGgIMzOzRs937NgxbNy4ETk5OQrn2Jzx69OpUydERUXVaX/rrbcwefJkAMDSpUuRkpKCtWvX4vPPP8eOHTtw//59bN26FTo6OgCA2NhYDB8+HJ9++mm939JFRkZi8eLFzc6PiIiIiOhF1q5dO6iqqtY7q13f79XAgxpg3759uH//Pm7dugULCwuEhYXJrZSdO3euMNsNAN26dcPly5cRGRkJf39/5VzMIzjTTQq5ePEiqqur4ebmJrQZGBjA3t5eLs7Dw6PO/sNZ4foUFhZCV1dX2JYvX47y8nK8++67WL9+Pdq1a1dvv+XLl8v1KywsfIKre8DFxaXe9sauKS8vD05OTkLBDTz44kEqlSI/P7/e8cLDw1FaWipsV65ceeLciYiIiIiedxoaGnBxcUFqaqrQJpVKAQC9evVqtK+WlhYsLS1RU1ODPXv2YMSIEcKxu3fvys18A4CqqqowtrJxpptalYWFhdxstpGRES5cuICCggIMHz5caH/4A6Gmpob8/HxMnToVo0ePlhunISoqKnXewVddXV0n7tHCWZk0NTWhqan5VM5FRERERPQ8CQkJgb+/P1xdXeHm5iasRH3nnXcAABMmTIClpSUiIyMBACdOnMDVq1fh7OyMq1evYtGiRZBKpQgNDRXGHD58OJYtWwZra2t06dIF2dnZiI6OxqRJk57KNbHoJoXY2NhAXV0dGRkZsLa2BgCUlpbizz//RN++fYW448ePy/U7fvw4HBwchH11dXXU1tYK+2pqarCzs5Pro62tjdOnT8u1zZ8/H+Xl5VizZg2srKygoaEBIyOjOnn+e3zgwZKTM2fOyLXl5ORAXV1dkUvH8ePHMWHCBLn9Hj16AAAcHBwQHx+PiooKoWhPS0uDiopKnVUARERERETUuDFjxuDGjRtYuHAhiouL0a1bNwCAiYkJgAcrZR+dtb5//z7mz5+PixcvQldXF0OGDEFCQgIMDQ2FmLVr12LBggWYPn06rl+/DgsLC7z//vtYuHDhU7kmFt2kED09Pfj7+2Pu3LkwMjKCiYkJIiIioKKiApFIJMSlpaUhKioKfn5+SElJwe7du5GYmCgcl0gkSE1NhaenJzQ1NdGmTZs659LS0kLXrl3l2h7+0Py7/d/qG3/AgAFYsWIFtm7dCg8PD2zbtg1nzpwRCuem7N69G66urujTpw+2b9+OkydPYuPGjQCA8ePHIyIiAv7+/li0aBFu3LiBmTNn4t13323wvhMiIiIiImpYUFCQ8GDisrIyGBgYCMcOHTokF9uvXz/k5uY2Op6enh5iYmKEd34/bbynmxQWHR0NDw8PDBs2DN7e3vD09ISDg4Pce/E+/PBDnDp1Cj169MDHH3+M6OhouddvrVq1CikpKbCyslK46G2O+sb38fHBggULEBoail69eqG8vFxu5ropixcvxs6dO9G9e3ds3boVX3/9NRwdHQE8mJVPTk7G33//jV69euHNN9/EwIEDERsb2+LXRkREREREzx+R7N83uxIpqKKiApaWlli1ahUCAwMhkUgQHBwsvLebFPPw27sBc76Amqa4tdMhIiIiIlKK5I8Vn/h66OHvyqWlpdDX11dCVsrH5eWksOzsbJw9exZubm4oLS3FkiVLAEDuyYBERERERET0f1h0U7OsXLkS+fn5wuP8jx492uBrvYiIiIiIiF52LLpJYT169EBmZmaDxwsKCp5eMkRERERERM8BPkiNiIiIiIiISElYdBMREREREREpCZeXEz0jvlsw7rl9IiMREREREdWPM91ERERERERESsKim4iIiIiIiEhJWHQTERERERERKQmLbiIiIiIiIiIlYdFNREREREREpCR8ejnRM+L1/34JNU1xa6dBRERERKQU/1sV1NoptArOdBMREREREREpCYtuIiIiIiIiIiVh0U1ERERERESkJCy6iYiIiIiIiJSERTcRERERERGRkrDoJmqCSCTCvn37FI6Pj4+HoaGh0vIhIiIiInqRxcXFQSKRQEtLCwMGDGg0trq6GkuWLIGtrS20tLTg5OSEpKQkuZja2losWLAAHTt2hFgshq2tLZYuXQqZTKbMyxCw6Kbn0qxZs+Di4gJNTU04Ozsr9VxFRUXw9fVVOH7MmDH4888/lZgREREREdGLadeuXQgJCUFERASysrLQtWtXAMCNGzfqjZ8/fz6+/PJLrF27Frm5uZg6dSpGjhyJ7OxsIebTTz/FunXrEBsbi7y8PHz66aeIiorC2rVrn8o1iWRPq7wnakGzZs2Cvb09Tpw4gd9//x05OTmtndJjKysrg4GBAfrNiOJ7uomIiIjohaXIe7rd3d3Rq1cvxMbGAgBu376NNm3aICIiAosWLaoTb2FhgXnz5mHGjBlC26hRoyAWi7Ft2zYAwLBhw2BqaoqNGzc2GKNMnOmmZ1JlZSVmzZoFExMTaGlpoU+fPsjIyBCOf/bZZ5gxYwZsbGwUHnPRokVwdnbGpk2bYG1tDV1dXUyfPh21tbWIioqCmZkZTExMsGzZMrl+jy4vLygogEgkwt69e9G/f39oa2vDyckJ6enpQjyXlxMRERERNV9VVRUyMzPh7e0ttKmoPChZH60FHlVZWQktLS25NrFYjGPHjgn7vXv3RmpqqrAa9bfffsOxY8eatZr1SbDopmdSaGgo9uzZgy1btiArKwt2dnbw8fHB33///UTjXrhwAT/99BOSkpLw9ddfY+PGjRg6dCj++usvHD58GJ9++inmz5+PEydONDrOvHnzMGfOHOTk5OCVV17BuHHjUFNT80S5ERERERG9zG7evIna2lqYmprWOVZSUlJvHx8fH0RHR+PcuXOQSqVISUnB3r17UVRUJMSEhYVh7Nix6Ny5M9TV1dGjRw8EBwdj/PjxSruWR7HopmdORUUF1q1bhxUrVsDX1xeOjo5Yv349xGKx3JKQxyGVSrFp0yY4Ojpi+PDh6N+/P/Lz8xETEwN7e3sEBATA3t4ev/zyS6PjzJkzB0OHDsUrr7yCxYsX4/Llyzh//rxCOVRWVqKsrExuIyIiIiKi5luzZg06deqEzp07Q0NDA0FBQQgICBBmyAHgm2++wfbt27Fjxw5kZWVhy5YtWLlyJbZs2fJUcmTRTc+cCxcuoLq6Gp6enkKburo63NzckJeXp9AYurq6wjZ16lShXSKRQE9PT9g3NTWFo6Oj3A+lqakprl+/3uj43bt3F/5sbm4OAE32eSgyMhIGBgbCZmVlpVA/IiIiIqIXWbt27aCqqlrvrHZ9s98AYGxsjH379qGiogKXL1/G2bNnoaurK3cb6ty5c4XZ7m7duuHdd9/F7NmzERkZqbRreZTaUzkL0VP26IPV9PX1hT+rq6vLxYlEonrbpFJpo+M/2kckEgFAk30eCg8PR0hIiLBfVlbGwpuIiIiIXnoaGhpwcXFBamoq/Pz8APzf79i9evVqtK+WlhYsLS1RXV2NPXv2YPTo0cKxu3fvyk2yAYCqqqrCv78/KRbd9MyxtbWFhoYG0tLS0KFDBwAP3r+XkZGB4OBghcaws7NTYoZPRlNTE5qamq2dBhERERHRMyckJAT+/v5wdXWFm5sboqKiAADvvPMOAGDChAmwtLQUZqlPnDiBq1evwtnZGVevXsWiRYsglUoRGhoqjDl8+HAsW7YM1tbW6NKlC7KzsxEdHY1JkyY9lWti0U3PHB0dHUybNg1z586FkZERrK2tERUVhbt37yIwMBAAcP78edy5cwfFxcW4d++eMLPt6OgIDQ2NVsyeiIiIiIge15gxY3Djxg0sXLgQxcXF6NatGwDAxMQEAFBYWCg3a33//n3Mnz8fFy9ehK6uLoYMGYKEhAS5twmtXbsWCxYswPTp03H9+nVYWFjg/fffx8KFC5/KNbHopmfSJ598AqlUinfffRfl5eVwdXVFcnIy2rRpAwCYPHkyDh8+LMT36NEDAHDp0iVIJJLWSJmIiIiIiFpAUFAQgoIevNO7rKwMBgYGwrFDhw7Jxfbr1w+5ubmNjqenp4eYmBjExMS0dKoKEclkMlmrnJmIAPzff0j6zYiCmqa4tdMhIiIiIlKK/60Kanafh78rl5aWyj2r6XnCp5cTERERERERKQmLbiIiIiIiIiIlYdFNREREREREpCQsuomIiIiIiIiUhEU3ERERERERkZKw6CYiIiIiIiJSEr6nm+gZsX/5+8/taxCIiIiIiKh+nOkmIiIiIiIiUhIW3URERERERERKwqKbiIiIiIiISElYdBMREREREREpCYtuIiIiIiIiIiXh08uJnhHDQlZBTUOrtdMgIiIiIlKKg5+Ht3YKrYIz3URERERERERKwqKbiIiIiIiISElYdBMREREREREpCYtuIiIiIiIiIiVh0U1ERERERESkJM9k0V1QUACRSIScnByln0sikSAmJkbp5yEiIiIiIqKmxcXFQSKRQEtLCwMGDGg0trq6GkuWLIGtrS20tLTg5OSEpKQkuZja2losWLAAHTt2hFgshq2tLZYuXQqZTKbMyxA8k0X382bv3r1wdXWFoaEhdHR04OzsjISEhNZOq0XEx8fD0NCwybi///4bM2fOhL29PcRiMaytrTFr1iyUlpbKxRUWFmLo0KHQ1taGiYkJ5s6di5qaGuH43r17MWjQIBgbG0NfXx8eHh5ITk5u8LyffPIJRCIRgoOD5drv37+PGTNmoG3bttDV1cWoUaNQUlIiHP/tt98wbtw4WFlZQSwWw8HBAWvWrJEbQ5FcysvLERwcjA4dOkAsFqN3797IyMho8vMiIiIiIqK6du3ahZCQEERERCArKwtdu3YFANy4caPe+Pnz5+PLL7/E2rVrkZubi6lTp2LkyJHIzs4WYj799FOsW7cOsbGxyMvLw6effoqoqCisXbv2qVwTi+4WYGRkhHnz5iE9PR2///47AgICEBAQ0Gix+KK5du0arl27hpUrV+LMmTOIj49HUlISAgMDhZja2loMHToUVVVV+PXXX7FlyxbEx8dj4cKFQsyRI0cwaNAgHDhwAJmZmejfvz+GDx8u90PzUEZGBr788kt07969zrHZs2fjhx9+wO7du3H48GFcu3YNb7zxhnA8MzMTJiYm2LZtG/744w/MmzcP4eHhiI2NbVYukydPRkpKChISEnD69GkMHjwY3t7euHr16hN/pkREREREL5vo6GhMmTIFAQEBcHR0FFYlNzSpmZCQgP/+978YMmQIbGxsMG3aNAwZMgSrVq0SYn799VeMGDECQ4cOhUQiwZtvvonBgwfj5MmTT+OSWrfolkqliIqKgp2dHTQ1NWFtbY1ly5bViautrUVgYKCwHMDe3r7OrKSXl1ed2U4/Pz9MnDhR2L9+/TqGDx8OsViMjh07Yvv27XXOdfv2bUyePFmY3RwwYAB+++23Rq/Dy8sLI0eOhIODA2xtbfHBBx+ge/fuOHbsWIN9ZDIZFi1aBGtra2hqasLCwgKzZs0Sjv/zzz+YMGEC2rRpA21tbfj6+uLcuXPC8Ycz0MnJyXBwcICuri5ee+01FBUVCTETJ06En58fVq5cCXNzc7Rt2xYzZsxAdXW1EFNZWYk5c+bA0tISOjo6cHd3x6FDhwAAhw4dQkBAAEpLSyESiSASibBo0aJ6r6dr167Ys2cPhg8fDltbWwwYMADLli3DDz/8IMxk//zzz8jNzcW2bdvg7OwMX19fLF26FHFxcaiqqgIAxMTEIDQ0FL169UKnTp2wfPlydOrUCT/88IPc+e7cuYPx48dj/fr1aNOmjdyx0tJSbNy4EdHR0RgwYABcXFywefNm/Prrrzh+/DgAYNKkSVizZg369esHGxsbvPPOOwgICMDevXuFcZrK5d69e9izZw+ioqLQt29f2NnZYdGiRbCzs8O6desa/LsnIiIiIqK6qqqqkJmZCW9vb6FNReVBydrQatLKykpoaWnJtYnFYrlarHfv3khNTcWff/4J4MGq12PHjsHX17elL6FerVp0h4eH45NPPsGCBQuQm5uLHTt2wNTUtE6cVCpF+/btsXv3buTm5mLhwoX473//i2+++aZZ55s4cSKuXLmCX375Bd9++y0+//xzXL9+XS7mrbfewvXr1/HTTz8hMzMTPXv2xMCBA/H3338rdA6ZTIbU1FTk5+ejb9++Dcbt2bMHq1evxpdffolz585h37596Natm1yup06dwv79+5Geng6ZTIYhQ4bIFcx3797FypUrkZCQgCNHjqCwsBBz5syRO88vv/yCCxcu4JdffhFmluPj44XjQUFBSE9Px86dO/H777/jrbfewmuvvYZz586hd+/eiImJgb6+PoqKilBUVFRn/MaUlpZCX18fampqAID09HR069ZN7u/Yx8cHZWVl+OOPP+odQyqVory8HEZGRnLtM2bMwNChQ+V+IB/KzMxEdXW13LHOnTvD2toa6enpjeb77/M0lktNTQ1qa2ub/CEnIiIiIqKm3bx5E7W1tfXWhI/eKvooHx8fREdH49y5c5BKpUhJScHevXvlJiPDwsIwduxYdO7cGerq6ujRoweCg4Mxfvx4pV3Lo9SeylnqUV5ejjVr1iA2Nhb+/v4AAFtbW/Tp0wcFBQVyserq6li8eLGw37FjR6Snp+Obb77B6NGjFTrfn3/+iZ9++gknT55Er169AAAbN26Eg4ODEHPs2DGcPHkS169fh6amJgBg5cqV2LdvH7799lu89957DY5fWloKS0tLVFZWQlVVFZ9//jkGDRrUYHxhYSHMzMzg7e0NdXV1WFtbw83NDQBw7tw57N+/H2lpaejduzcAYPv27bCyssK+ffvw1ltvAXjw0IAvvvgCtra2AB4U0EuWLJE7T5s2bRAbGwtVVVV07twZQ4cORWpqKqZMmYLCwkJs3rwZhYWFsLCwAADMmTMHSUlJ2Lx5M5YvXw4DAwOIRCKYmZkp9Dk/dPPmTSxdulTuMysuLq7zA/Rwv7i4uN5xVq5ciTt37sj9Pe/cuRNZWVkNfttVXFwMDQ2NOveim5qaNnieX3/9Fbt27UJiYmKD1/TvXPT09ODh4YGlS5fCwcEBpqam+Prrr5Geng47O7sGx6msrERlZaWwX1ZW1mAsERERERE1bM2aNZgyZQo6d+4MkUgEW1tbBAQEYNOmTULMN998g+3bt2PHjh3o0qULcnJyEBwcDAsLC6EWVaZWm+nOy8tDZWUlBg4cqFB8XFwcXFxcYGxsDF1dXXz11VcoLCxs1vnU1NTg4uIitHXu3FmuMPvtt99w584d4eFbD7dLly7hwoULKCwslGtfvny50FdPTw85OTnIyMjAsmXLEBISIizTXr58uVy/wsJCvPXWW7h37x5sbGwwZcoUfPfdd8Iy7Ie5uru7C+O3bdsW9vb2yMvLE9q0tbWFghsAzM3N68zcd+nSBaqqqvXGnD59GrW1tXjllVfk8jt8+DAuXLjQ4GdZ3/U8qqysDEOHDoWjo2ODy9EVsWPHDixevBjffPMNTExMAABXrlzBBx98gO3bt9eZYX5cZ86cwYgRIxAREYHBgwcrnAvw4B4SmUwGS0tLaGpq4rPPPsO4ceOEZTD1iYyMhIGBgbBZWVm1yHUQERERET3P2rVrB1VV1Xpnteub/QYAY2Nj7Nu3DxUVFbh8+TLOnj0LXV1d2NjYCDFz584VZru7deuGd999F7Nnz0ZkZKTSruVRrTbTLRaLFY7duXMn5syZg1WrVsHDwwN6enpYsWIFTpw4IcSoqKjUeeT7o0uxFXHnzh2Ym5sLxfKjDA0NYWhoKPcas0eXIquoqAizm87OzsjLy0NkZCS8vLwwdepUuZlaCwsLqKmpIT8/H//73/+QkpKC6dOnY8WKFTh8+LDC+aqrq8vti0SiOp9BfTFSqVS4XlVVVWRmZsoV5gCgq6vb4Hnru56HysvL8dprr0FPTw/fffed3PnNzMzqPKzg4Q/Uv2fSd+7cicmTJ2P37t1yy8QzMzNx/fp19OzZU2irra3FkSNHEBsbi8rKSpiZmaGqqgq3b9+W+1KlpKSkznlyc3MxcOBAvPfee5g/f36919tQLsCD1RmHDx9GRUUFysrKYG5ujjFjxsj9kP9beHg4QkJChP2ysjIW3kRERET00tPQ0ICLiwtSU1Ph5+cHAELt8nC1ckO0tLRgaWmJ6upq7NmzR65euXv3bp1JMVVVVWFsZWu1ortTp04Qi8VITU3F5MmTG419uMx6+vTpQtu/Z2KNjY3l1u3X1tbizJkz6N+/P4AHs9o1NTXIzMwU/sLy8/Nx+/ZtoU/Pnj1RXFwMNTU1SCSSenNpbNnwo6RSqbCE2MjIqN57hcViMYYPH47hw4djxowZ6Ny5M06fPg0HBwfU1NTgxIkTwvLyW7duIT8/H46OjgqdXxE9evRAbW0trl+/jldffbXeGA0NDdTW1sq1NXQ9ZWVl8PHxgaamJvbv319nJtrDwwPLli3D9evXhdnilJQU6Ovry13X119/jUmTJmHnzp0YOnSo3BgDBw7E6dOn5doCAgLQuXNnfPTRR1BVVYWLiwvU1dWRmpqKUaNGAXjwd11YWAgPDw+h3x9//IEBAwbA39+/3gf4NZXLo3R0dKCjo4N//vkHycnJiIqKajBWU1NTuH2BiIiIiIj+T0hICPz9/eHq6go3Nzfh9+p33nkHADBhwgRYWloKs9QnTpzA1atX4ezsjKtXr2LRokWQSqUIDQ0Vxhw+fDiWLVsGa2trdOnSBdnZ2YiOjsakSZOeyjW1WtGtpaWFjz76CKGhodDQ0ICnpydu3LiBP/74o86S806dOmHr1q1ITk5Gx44dkZCQgIyMDHTs2FGIGTBgAEJCQpCYmAhbW1tER0fLFdT29vZ47bXX8P7772PdunVQU1NDcHCw3Iy7t7c3PDw84Ofnh6ioKLzyyiu4du0aEhMTMXLkSLi6utZ7LZGRkXB1dYWtrS0qKytx4MABJCQkNPoE6/j4eNTW1sLd3R3a2trYtm0bxGIxOnTogLZt22LEiBGYMmUKvvzyS+jp6SEsLAyWlpYYMWLEY37idb3yyisYP348JkyYgFWrVqFHjx64ceMGUlNT0b17d+GR+nfu3EFqaiqcnJygra0NbW3tOmOVlZVh8ODBuHv3LrZt24aysjLhXmVjY2Ooqqpi8ODBcHR0xLvvvouoqCgUFxdj/vz5mDFjhlCE7tixA/7+/lizZg3c3d2Fe7DFYjEMDAygp6cnvKvvIR0dHbRt21ZoNzAwQGBgIEJCQmBkZAR9fX3MnDkTHh4e+M9//gPgwZLyAQMGwMfHByEhIcJ5VFVVYWxsrFAuAJCcnAyZTAZ7e3ucP38ec+fORefOnREQENBif09ERERERC+LMWPG4MaNG1i4cCGKi4uFh00/nLQrLCyUm7W+f/8+5s+fj4sXL0JXVxdDhgxBQkKC3IrXtWvXYsGCBZg+fTquX78OCwsLvP/++3KvLlamVn16+YIFC/Dhhx9i4cKFcHBwwJgxY+rckwwA77//Pt544w2MGTMG7u7uuHXrltysN/DgFVD+/v6YMGGC8Bqoh7PcD23evBkWFhbo168f3njjDbz33nty9+eKRCIcOHAAffv2RUBAAF555RWMHTsWly9fbvAeAgCoqKjA9OnT0aVLF3h6emLPnj3Ytm1bozP4hoaGWL9+PTw9PdG9e3f873//ww8//IC2bdsKubq4uGDYsGHw8PCATCbDgQMH6iwXf1KbN2/GhAkT8OGHH8Le3h5+fn7IyMiAtbU1gAeP1586dSrGjBkDY2PjBmdws7KycOLECZw+fRp2dnYwNzcXtitXrgB4UND++OOPUFVVhYeHB9555x1MmDBB7uFvX331FWpqajBjxgy5MT744INmXdfq1asxbNgwjBo1Cn379oWZmZnc68C+/fZb3LhxA9u2bZM7z6PLVhTJpbS0VFilMGHCBPTp0wfJyckt/vdERERERPSyCAoKwuXLl1FZWYmDBw/KHTt06JDc25j69euH3Nxc3L9/Hzdv3sTWrVvlbn8FHjx/KyYmBpcvX8a9e/dw4cIFfPzxx9DQ0HgalwOR7N83ARPRU1VWVgYDAwO8GrgQahot83A4IiIiIqJnzcHPw5vd5+Hvyg9fR/w8atWZbiIiIiIiIqIXGYtuIiIiIiIiIiVh0U1ERERERESkJCy6iYiIiIiIiJSERTcRERERERGRkrTae7qJSN6P0R8+t09kJCIiIiKi+nGmm4iIiIiIiEhJWHQTERERERERKQmLbiIiIiIiIiIlYdFNREREREREpCQsuomIiIiIiIiUhE8vJ3pGDJm2CGoamq2dBhERERHRYzm0ObK1U3gmcaabiIiIiIiISElYdBMREREREREpCYtuIiIiIiIiIiVh0U1ERERERESkJCy6iYiIiIiIiJSERTcRERERERE9NXFxcZBIJNDS0oK7uztOnjzZYGx1dTUAwMnJCVpaWnByckJSUpJcjEQigUgkqrPNmDFDqdehKBbdLxCRSIR9+/a1dhpERERERET12rVrF0JCQhAREYGsrCw4OTnBx8cH169frzd+6dKlAIAVK1YgNzcXU6dOxciRI5GdnS3EZGRkoKioSNhSUlIAAG+99ZbyL0gBLLob8ThF7M6dOyESieDn56eU8VvD3r17MWjQIBgbG0NfXx8eHh5ITk6uE9fYN1Z///03Zs6cCXt7e4jFYlhbW2PWrFkoLS2t95y3bt1C+/btIRKJcPv27SZz3L17Nzp37gwtLS1069YNBw4caDB26tSpEIlEiImJaXLcwsJCDB06FNra2jAxMcHcuXNRU1NT57odHBwgFothb2+PrVu3NjkuEREREdHLKDo6GlOmTEFAQAAcHR3xxRdfQFtbG5s2bao3fteuXQCAwYMHw8bGBtOmTcOQIUOwatUqIcbY2BhmZmbC9uOPP8LW1hb9+vV7KtfUFBbdLaigoABz5szBq6+++lTPW1VVpdTxjxw5gkGDBuHAgQPIzMxE//79MXz4cLlvl5r6xuratWu4du0aVq5ciTNnziA+Ph5JSUkIDAys95yBgYHo3r27Qvn9+uuvGDduHAIDA5GdnQ0/Pz/4+fnhzJkzdWK/++47HD9+HBYWFk2OW1tbi6FDh6Kqqgq//vortmzZgvj4eCxcuFCIWbduHcLDw7Fo0SL88ccfWLx4MWbMmIEffvhBodyJiIiIiF4WVVVVyMzMhLe3t9CmoqICb29vpKen19unsrKyTptYLMaxY8caPMe2bdswadIkiESilkn8Cb2wRXd5eTnGjx8PHR0dmJubY/Xq1fDy8kJwcDCAB+v+ly5dinHjxkFHRweWlpaIi4sT+kskEgDAyJEjIRKJhP2G1NbWYvz48Vi8eDFsbGyazK+h8SdOnFhnljw4OBheXl7CvpeXF4KCghAcHIx27drBx8dHOFZUVARfX1+IxWLY2Njg22+/lRvr9OnTGDBgAMRiMdq2bYv33nsPd+7caTTXmJgYhIaGolevXujUqROWL1+OTp06yRWWTX1j1bVrV+zZswfDhw+Hra0tBgwYgGXLluGHH36oM3O8bt063L59G3PmzGnycwSANWvW4LXXXsPcuXPh4OCApUuXomfPnoiNjZWLu3r1KmbOnInt27dDXV29yXF//vln5ObmYtu2bXB2doavry+WLl2KuLg44YuOhIQEvP/++xgzZgxsbGwwduxYvPfee/j0008Vyp2IiIiI6GVx8+ZN1NbWwtTUVK7d1NQUxcXF9fYZOHAgAODChQuQSqVISUnB3r17UVRUVG/8vn37cPv2bUycOLFFc38SL2zRHRISgrS0NOzfvx8pKSk4evQosrKy5GJWrPh/7d17XI73/wfw1113ZyoRlaFUKscoUjEhyizyncOarw7KYbKhOcyhQoRU0+Y0pxymRWZmhCX6bsipZDMth0mbVA7raCp1//7o0fVzuYsyt8pez8fjfjzcn+tzfQ5Xl/u+39fn87mu1ejRowcuXbqETz/9FDNmzBDm/1+4cAEAEB0djbt37wrva7N06VK0bt261pHbZ9W3/Gft2LEDqqqqOH36NDZu3CikBwYG4r333sPly5cxfvx4vP/++0hPTwcAlJSUwMXFBS1atMCFCxcQFxeH48ePY/r06fWqu7KyEkVFRdDT0wPwclesAKCgoADa2tqQSqVC2tWrV7F06VLs3LkTSkp1Oz2Tk5NFdQOAi4uLqO7KykpMmDABc+bMQZcuXepcbrdu3UQfCi4uLigsLMSvv/4KoOrKm7q6umg/DQ0NnD9/Xrjpw7NKS0tRWFgoehERERERkbzqwSxbW1uoqqpi+vTp8PHxqTVW2Lp1K4YNG1anma2vyxsZdBcVFWHHjh0IDw/H4MGD0bVrV0RHR6OiokKUz9HREZ9++ik6deqEjz76CKNHj8Znn30GoGpdAADo6urCwMBAeF+TU6dOYevWrdi8eXOd21if8mtibm6OsLAwWFhYwMLCQkgfM2YM/Pz80KlTJ4SEhMDW1hZffPEFACAmJgaPHz/Gzp070bVrVwwaNAhr167Frl27kJubW+e6w8PDUVxcjLFjxwJ4uStW9+/fR0hICCZPniyklZaWwsPDA6tXr0b79u3r3J6cnJwX1r1q1SpIpVJ8/PHH/7jc6m1AVRC+ZcsWpKSkQCaT4eLFi9iyZQvKy8tx//79GstdsWIFdHR0hFe7du3q3CYiIiIioqaqVatWUFZWlos9cnNzYWBgUOs+QNWM3tu3b+O3335Ds2bNapxdfPv2bRw/fhx+fn6vvvH/wBsZdP/+++8oLy9Hnz59hDQdHR1RcAoA9vb2cu+rR4VrkpWVhWbNmgmv0NBQFBUVYcKECdi8ebNwQjwrNDRUtF9WVtY/6F0VGxubGtOf16f09HT06NEDWlpawnZHR0dUVlYiIyMDAETtnDp1qlz5MTExWLJkCfbu3YvWrVu/VNsLCwsxfPhwdO7cGYsXLxbS58+fDysrK/z3v/+tcb+ajn9dpKSkICoqCtu3b691XcewYcOEcus6Eg5UzSwYNmwY+vbtCxUVFYwcORJeXl4AUOvVt/nz56OgoEB4/fHHH3Wuj4iIiIioqVJVVYWNjQ0SExOFtMrKSiQmJsrFMc9SV1dH27Zt8eTJE3zzzTcYOXKkXJ7o6Gi0bt0aw4cPf+Vt/yekL85C1YyMjJCWlia819PTw82bN5GZmQk3NzchvbKyEgAglUqRkZGBqVOnCqPC1eXURklJCTKZTJRW0zTlpwPnV+np/mlra4u2xcbGws/PD3FxcaLp3PW5YlVUVARXV1c0b94c3377rWht9YkTJ/DLL78I69Crj0OrVq2wcOFCBAYGyh1/ADAwMHhu3T/99BPy8vJEo+cVFRX45JNPsGbNGmRmZmLLli34+++/AUBok4GBgdwzA6vrqS5bQ0MD27Ztw5dffonc3FwYGhpi06ZNaN68ea2zF9TU1KCmplbjNiIiIiKiN1lAQAC8vLxga2uLPn36YM2aNSgpKYGPjw8AwNPTE23btsWKFSsAABcvXgQA3Lp1C4WFhVi8eDEqKysxd+5cUbmVlZWIjo6Gl5eXaPlqY9C4WvOKdOzYESoqKrhw4YIQaBUUFODatWt4++23hXxnz54V7Xf27FlYWVkJ71VUVERT0qVSKczMzET7aGpq4pdffhGlLVq0CEVFRYiKikK7du2gqqoqBIhPe7Z8oGra+bN33U5LS6vTjb+q++Dp6Sl637NnTwCAlZUVtm/fjpKSEiFoP336NJSUlIRZAM/2r9rXX3+NiRMnIjY2Vu7K0dNXrKpvAld9xerp9eKFhYVwcXGBmpoaDh48KLcW+ptvvhECX6Bq3fvEiRPx008/wdTUtMbjD1SN5icmJgo3yQOAhIQE4WrZhAkTalzzPWHCBOE/d9u2bWssd/ny5cjLyxNG9RMSEqCtrY3OnTuL8qqoqOCtt94CUHVx4t13363zmnQiIiIion+LcePG4d69ewgKCkJOTg6sra1x9OhRYRlnVlaW6Hf048ePAQB2dnZo1qwZ3nnnHezatQu6urqico8fP46srCxMnDjxtfWlrt7IoLt58+bw8vLCnDlzoKenh9atWyM4OBhKSkqi6cWnT59GWFgY3N3dkZCQgLi4OBw+fFjYbmxsjMTERDg6OkJNTQ0tWrSQq0tdXR1du3YVpVWfAM+mP6um8gcNGoTVq1dj586dsLe3x1dffYUrV64IgfOLxMXFwdbWFv369cPu3btx/vx5bN26FQAwfvx4BAcHw8vLC4sXL8a9e/fw0UcfYcKECXJrl58WExMDLy8vREVFwc7OTljPrKGhAR0dHQAvvmJVWFiIoUOH4tGjR/jqq69ENxDT19eHsrIyTE1NRfVWr4m2srKS+0/1tBkzZmDAgAGIiIjA8OHDERsbi4sXL2LTpk0AgJYtW6Jly5aifVRUVGBgYCC35OBpQ4cORefOnTFhwgSEhYUhJycHixYtgr+/vzBSfe3aNZw/fx52dnb466+/EBkZiStXrmDHjh21lktERERE9G82ffr0Wm/mnJSUJHrfr18/AEBeXp7cTNynDR06VG7GcGPxxg7FRUZGwt7eHu+++y6cnZ3h6OgIKysr0ejqJ598gosXL6Jnz55YtmwZIiMjRY/fioiIQEJCAtq1a1fnoLc+airfxcUFgYGBwiO6ioqKRCPXL7JkyRLExsaie/fu2LlzJ77++mthVFZTUxPHjh3Dw4cP0bt3b4wePRqDBw+We7TWszZt2oQnT57A398fhoaGwmvGjBlCnnHjxiE8PBxBQUGwtrZGWlqa6IpVamoqzp07h19++QVmZmaicv7pmmYHBwfExMRg06ZN6NGjB/bt24cDBw688KLHiygrK+PQoUNQVlaGvb09/vvf/8LT0xNLly4V8lRUVCAiIgI9evTAkCFD8PjxY5w5c+aFj5gjIiIiIqJ/B4mssV4OeMVKSkrQtm1bREREwNfXF8bGxpg5c6ZoSjJRQygsLISOjg4cP5gFqSrXehMRERFR05QUveKVl1n9W7n6ccNN0Rs5vRwALl26hN9++w19+vRBQUGBMDpZ013uiIiIiIiIiBThjQ26garnSWdkZAg3+vrpp59qfawXERERERER0av2xgbdPXv2REpKSq3bMzMzX19jiIiIiIiI6F/pjb2RGhEREREREVFDY9BNREREREREpCBv7PRyoqYmfsPiJntHRiIiIiIiqhlHuomIiIiIiIgUhEE3ERERERERkYIw6CYiIiIiIiJSEAbdRERERERERArCoJuIiIiIiIhIQXj3cqJGwsXnE0hVVBu6GURERESv3U+x6xq6CUQKw5FuIiIiIiIiIgVh0E1ERERERESkIAy6iYiIiIiIiBSEQTcRERERERGRgjDoJiIiIiIiIlKQNyrozszMhEQiQVpamsLrMjY2xpo1axReDxERERERVVm3bh2MjY2hrq4OOzs7nD9//rn516xZAwsLC2hoaKBdu3aYNWsWHj9+LGz/8ccf4ebmBiMjI0gkEhw4cEDBPaB/ozcq6G5q9u/fD1tbW+jq6kJLSwvW1tbYtWtXQzfrpW3evBn9+/dHixYt0KJFCzg7O8t9EMpkMgQFBcHQ0BAaGhpwdnbG9evXhe2ZmZnw9fWFiYkJNDQ0YGpqiuDgYJSVldVY540bN9C8eXPo6urKbYuLi4OlpSXU1dXRrVs3xMfHC9vKy8sxb948dOvWDVpaWjAyMoKnpyeys7Pr3Za9e/fC2toampqa6NChA1avXv0yh4+IiIiInmPPnj0ICAhAcHAwUlNT0aNHD7i4uCAvL6/G/DExMfj0008RHByM9PR0bN26FXv27MGCBQuEPCUlJejRowfWreMjy0hxGHQ3ID09PSxcuBDJycn4+eef4ePjAx8fHxw7dqyhm/ZSkpKS4OHhgZMnTyI5ORnt2rXD0KFDcefOHSFPWFgYPv/8c2zcuBHnzp2DlpYWXFxchCuOv/32GyorK/Hll1/i119/xWeffYaNGzeKPhyrlZeXw8PDA/3795fbdubMGXh4eMDX1xeXLl2Cu7s73N3dceXKFQDAo0ePkJqaisDAQKSmpmL//v3IyMjAiBEjhDLq0pYjR45g/PjxmDp1Kq5cuYL169fjs88+w9q1a1/ZcSUiIiIiIDIyEpMmTYKPjw86d+6MjRs3QlNTE9u2basx/5kzZ+Do6IgPPvgAxsbGGDp0KDw8PESDQsOGDcOyZcswatSo19UN+hdqkkF3ZWUlwsLCYGZmBjU1NbRv3x7Lly+Xy1dRUSEaqbSwsEBUVJQoj5OTE2bOnClKc3d3h7e3t/A+Ly8Pbm5u0NDQgImJCXbv3i1XV35+Pvz8/KCvrw9tbW0MGjQIly9ffm4/nJycMGrUKFhZWcHU1BQzZsxA9+7dcerUqefuV1paio8//hitW7eGuro6+vXrhwsXLgjbk5KSIJFIcPjwYXTv3h3q6uro27evEHACwOLFi2FtbS0qd82aNTA2NhaV06dPH2hpaUFXVxeOjo64fft2re3avXs3pk2bBmtra1haWmLLli2orKxEYmIigKpR7jVr1mDRokUYOXIkunfvjp07dyI7O1uYyuPq6oro6GgMHToUHTt2xIgRIzB79mzs379frr5FixbB0tISY8eOldsWFRUFV1dXzJkzB1ZWVggJCUGvXr2EYFhHRwcJCQkYO3YsLCws0LdvX6xduxYpKSnIysqqc1t27doFd3d3TJ06FR07dsTw4cMxf/58rFq1CjKZrNZjRURERER1V1ZWhpSUFDg7OwtpSkpKcHZ2RnJyco37ODg4ICUlRQiyf//9d8THx+Odd955LW0mqtYkg+758+dj5cqVCAwMxNWrVxETE4M2bdrI5ausrMRbb72FuLg4XL16FUFBQViwYAH27t1br/q8vb3xxx9/4OTJk9i3bx/Wr18vN41lzJgxyMvLw5EjR5CSkoJevXph8ODBePjwYZ3qkMlkSExMREZGBt5+++3n5p07dy6++eYb7NixA6mpqTAzM4OLi4tcXXPmzEFERAQuXLgAfX19uLm5oby8vE7tefLkCdzd3TFgwAD8/PPPSE5OxuTJkyGRSOq0P1A1mlxeXg49PT0AwK1bt5CTkyP6sNTR0YGdnV2tH5YAUFBQIJRR7cSJE4iLi6t1KlBycrKoHgBwcXF5YT0SiaTGqeq1taW0tBTq6uqiPBoaGvjzzz+fe4GCiIiIiOru/v37qKiokPvN36ZNG+Tk5NS4zwcffIClS5eiX79+UFFRgampKZycnGqcQUmkSE0u6C4qKkJUVBTCwsLg5eUFU1NT9OvXD35+fnJ5VVRUsGTJEtja2sLExATjx4+Hj49PvYLua9eu4ciRI9i8eTP69u0LGxsbbN26FX///beQ59SpUzh//jzi4uJga2sLc3NzhIeHQ1dXF/v27Xtu+QUFBWjWrBlUVVUxfPhwfPHFFxgyZEit+UtKSrBhwwasXr0aw4YNQ+fOnbF582ZoaGhg69atorzBwcEYMmQIunXrhh07diA3NxfffvttnfpdWFiIgoICvPvuuzA1NYWVlRW8vLzQvn37Ou0PAPPmzYORkZEQ/FZ/INbnw/LGjRv44osvMGXKFCHtwYMH8Pb2xvbt26GtrV3jfjk5OfWq5/Hjx5g3bx48PDxqLbOmtri4uGD//v1ITExEZWUlrl27hoiICADA3bt3ayyntLQUhYWFohcRERERvVpJSUkIDQ3F+vXrheWEhw8fRkhISEM3jf5lmlzQnZ6ejtLSUgwePLhO+detWwcbGxvo6+ujWbNm2LRpkzB9uK71SaVS2NjYCGmWlpai0dDLly+juLgYLVu2RLNmzYTXrVu3cPPmTWRlZYnSQ0NDhX2bN2+OtLQ0XLhwAcuXL0dAQACSkpIAAKGhoaL9srKycPPmTZSXl8PR0VEoQ0VFBX369EF6erqo7fb29sK/9fT0YGFhIZenNnp6evD29oaLiwvc3NwQFRUlBJHP60+1lStXIjY2Ft9++63cSHBd3blzB66urhgzZgwmTZokpE+aNAkffPDBC2cE1FV5eTnGjh0LmUyGDRs21Lst06dPx7vvvgtVVVX07dsX77//PoCqKU81WbFiBXR0dIRXu3btXkk/iIiIiN5UrVq1grKyMnJzc0Xpubm5MDAwqHGfwMBATJgwAX5+fujWrRtGjRqF0NBQrFixApWVla+j2UQAAGlDN6C+NDQ06pw3NjYWs2fPRkREBOzt7dG8eXOsXr0a586dE/IoKSnJrb2t6xTsasXFxTA0NBSC5afp6upCV1dX9Bizp6cnKykpwczMDABgbW2N9PR0rFixAk5OTpg6dapovbKRkRHy8/Pr1bba1KXf0dHR+Pjjj3H06FHs2bMHixYtQkJCAmxtbWvtDwCEh4dj5cqVOH78OLp37y6kV38g5ubmwtDQUEjPzc2VW1+enZ2NgQMHwsHBAZs2bRJtO3HiBA4ePIjw8HAAVVPzKysrIZVKsWnTJkycOBEGBgZ1+lCuDrhv376NEydO1DjK/by2SCQSrFq1CqGhocjJyYG+vr6whr1jx45yZQFVyyMCAgKE94WFhQy8iYiIiJ5DVVUVNjY2SExMhLu7OwAI9w6aPn16jfs8evRIbhBEWVkZAHjvHXqtmlzQbW5uDg0NDSQmJtY4pfxpp0+fhoODA6ZNmyak3bx5U5RHX19fNA24oqICV65cwcCBAwFUjWo/efIEKSkp6N27NwAgIyNDFPz26tULOTk5kEqlohuRPa06sH6RyspKlJaWAqgKZp8NaE1NTaGqqorTp0+jQ4cOAKoCxwsXLsjdEO7s2bPCdPC//voL165dg5WVldDvnJwcyGQyYZ12Tc8379mzJ3r27In58+fD3t4eMTEx6Nu3b639CQsLw/Lly3Hs2DHY2tqKtpmYmMDAwACJiYlCkF1YWIhz587hww8/FPLduXMHAwcOhI2NDaKjo+U+LJOTk1FRUSG8/+6777Bq1SqcOXMGbdu2BVA1yp+YmCg6JgkJCaLR/+qA+/r16zh58iRatmwp158XtaWasrKyUPfXX38Ne3t76Ovr15hXTU0NampqNW4jIiIiopoFBATAy8sLtra26NOnD9asWYOSkhL4+PgAADw9PdG2bVusWLECAODm5obIyEj07NkTdnZ2uHHjBgIDA+Hm5iYE38XFxbhx44ZQx61bt5CWlgY9Pb16Laskep4mF3Srq6tj3rx5mDt3LlRVVeHo6Ih79+7h119/lZtybm5ujp07d+LYsWMwMTHBrl27cOHCBZiYmAh5Bg0ahICAABw+fBimpqaIjIwUBdQWFhZwdXXFlClTsGHDBkilUsycOVM04u7s7Ax7e3u4u7sjLCwMnTp1QnZ2Ng4fPoxRo0bJBZ/VVqxYAVtbW5iamqK0tBTx8fHYtWtXrVOcAUBLSwsffvgh5syZI3wYhIWF4dGjR/D19RXlXbp0KVq2bIk2bdpg4cKFaNWqlXBl0MnJCffu3UNYWBhGjx6No0eP4siRI8JI761bt7Bp0yaMGDECRkZGyMjIwPXr1+Hp6Vlr21atWoWgoCDExMTA2NhYWD9dPQ1dIpFg5syZWLZsGczNzWFiYoLAwEAYGRkJ7bpz5w6cnJzQoUMHhIeH4969e0L51aPU1RcOql28eBFKSkro2rWrkDZjxgwMGDAAERERGD58OGJjY3Hx4kVhpLq8vByjR49GamoqDh06hIqKCqG9enp6UFVVrVNb7t+/j3379sHJyQmPHz9GdHQ04uLi8L///a/W40RERERE9Tdu3Djcu3cPQUFByMnJgbW1NY4ePSrcxycrK0s0QLJo0SJIJBIsWrQId+7cEW4s/PRTjy5evCgMtgEQZiN6eXlh+/btr6dj9MZrckE3ULU+QyqVIigoCNnZ2TA0NMTUqVPl8k2ZMgWXLl3CuHHjIJFI4OHhgWnTpuHIkSNCnokTJ+Ly5cvw9PSEVCrFrFmzRP/xgKpp1n5+fhgwYADatGmDZcuWITAwUNgukUgQHx+PhQsXwsfHB/fu3YOBgQHefvvtGu+qXq2kpATTpk3Dn3/+CQ0NDVhaWuKrr77CuHHjntv/lStXorKyEhMmTEBRURFsbW1x7NgxtGjRQi7fjBkzcP36dVhbW+P777+HqqoqgKrAdf369QgNDUVISAjee+89zJ49WwhKNTU18dtvv2HHjh148OABDA0N4e/vL7qJ2LM2bNiAsrIyjB49WpQeHByMxYsXA6i683pJSQkmT56M/Px89OvXD0ePHhXWfSckJODGjRu4ceMG3nrrLVE59ZkG5ODggJiYGCxatAgLFiyAubk5Dhw4IATmd+7cwcGDBwFAbmr7yZMn4eTkVOe27NixA7Nnz4ZMJoO9vb3wqDUiIiIierWmT59e63TyZ5d6SqVSBAcHIzg4uNbynJycONWcFE4i41n2xklKSsLAgQPx119/PffxV9Q4FBYWQkdHB33/4wepimpDN4eIiIjotfsptubHwBJV/1YuKCio9SlDjV2Tu3s5ERERERERUVPBoJuIiIiIiIhIQZrkmm56Pq5NISIiIiIiahw40k1ERERERESkIAy6iYiIiIiIiBSEQTcRERERERGRgnBNN1EjcSw6osk+BoGIiIiIiGrGkW4iIiIiIiIiBWHQTURERERERKQgDLqJiIiIiIiIFIRBNxEREREREZGCMOgmIiIiIiIiUhDevZyokRjy/iRIVVQbuhlERET0mp3+bldDN4GIFIgj3UREREREREQKwqCbiIiIiIiISEEYdBMREREREREpCINuIiIiIiIiIgVh0E1ERERERESkIG9U0J2ZmQmJRIK0tDSF12VsbIw1a9YovB4iIiIiIgBYt24djI2Noa6uDjs7O5w/f77WvE5OTpBIJHKv4cOHAwDKy8sxb948dOvWDVpaWjAyMoKnpyeys7NfV3eI/jXeqKCbXr0HDx7grbfegkQiQX5+/nPzbt68Gf3790eLFi3QokULODs7y30ZyGQyBAUFwdDQEBoaGnB2dsb169eF7ZmZmfD19YWJiQk0NDRgamqK4OBglJWVifLU9CVy9uxZUV1xcXGwtLSEuro6unXrhvj4eNF2b29vuTJcXV1FeZYvXw4HBwdoampCV1f3lR0rIiIiovrYs2cPAgICEBwcjNTUVPTo0QMuLi7Iy8urMf/+/ftx9+5d4XXlyhUoKytjzJgxAIBHjx4hNTUVgYGBSE1Nxf79+5GRkYERI0a8zm4R/Ssw6Kbn8vX1Rffu3euUNykpCR4eHjh58iSSk5PRrl07DB06FHfu3BHyhIWF4fPPP8fGjRtx7tw5aGlpwcXFBY8fPwYA/Pbbb6isrMSXX36JX3/9FZ999hk2btyIBQsWyNV3/Phx0ZeJjY2NsO3MmTPw8PCAr68vLl26BHd3d7i7u+PKlSuiMlxdXUVlfP3116LtZWVlGDNmDD788MNXeqyIiIiI6iMyMhKTJk2Cj48POnfujI0bN0JTUxPbtm2rMb+enh4MDAyEV0JCAjQ1NYWgW0dHBwkJCRg7diwsLCzQt29frF27FikpKcjKynqdXSN64zXJoLuyshJhYWEwMzODmpoa2rdvj+XLl8vlq6ioEI2aWlhYICoqSpTHyckJM2fOFKW5u7vD29tbeJ+Xlwc3NzdoaGjAxMQEu3fvlqsrPz8ffn5+0NfXh7a2NgYNGoTLly+/sC/ffPMNunTpAjU1NRgbGyMiIkK03djYGCEhIfDw8ICWlhbatm2LdevWCdtrmlKfn58PiUSCpKQkAMBff/2F8ePHQ19fHxoaGjA3N0d0dPQL27Zhwwbk5+dj9uzZL8wLALt378a0adNgbW0NS0tLbNmyBZWVlUhMTARQNcq9Zs0aLFq0CCNHjkT37t2xc+dOZGdn48CBAwCqguDo6GgMHToUHTt2xIgRIzB79mzs379frr6WLVuKvkxUVFSEbVFRUXB1dcWcOXNgZWWFkJAQ9OrVC2vXrhWVoaamJiqjRYsWou1LlizBrFmz0K1bt1d6rIiIiIjqqqysDCkpKXB2dhbSlJSU4OzsjOTk5DqVsXXrVrz//vvQ0tKqNU9BQQEkEskLZ/cRUf00yaB7/vz5WLlyJQIDA3H16lXExMSgTZs2cvkqKyvx1ltvIS4uDlevXkVQUBAWLFiAvXv31qs+b29v/PHHHzh58iT27duH9evXy03lGTNmDPLy8nDkyBGkpKSgV69eGDx4MB4+fFhruSkpKRg7dizef/99/PLLL1i8eDECAwOxfft2Ub7Vq1ejR48euHTpEj799FPMmDEDCQkJdW5/9XE6cuQI0tPTsWHDBrRq1eq5+1y9ehVLly7Fzp07oaT0cqfJo0ePUF5eDj09PQDArVu3kJOTI/rC0NHRgZ2d3XO/MAoKCoQynjZixAi0bt0a/fr1w8GDB0XbkpOTRfUAgIuLi1w9SUlJaN26NSwsLPDhhx/iwYMH9e7nqzhWRERERLW5f/8+Kioq5H7vtmnTBjk5OS/c//z587hy5Qr8/PxqzfP48WPMmzcPHh4e0NbW/sdtJqL/J23oBtRXUVERoqKisHbtWnh5eQEATE1N0a9fP2RmZoryqqioYMmSJcJ7ExMTJCcnY+/evRg7dmyd6rt27RqOHDmC8+fPo3fv3gCqrhRaWVkJeU6dOoXz588jLy8PampqAIDw8HAcOHAA+/btw+TJk2ssOzIyEoMHD0ZgYCAAoFOnTrh69SpWr14tGml3dHTEp59+KuQ5ffo0PvvsMwwZMqROfcjKykLPnj1ha2sLoGr0/HlKS0vh4eGB1atXo3379vj999/rVM+z5s2bByMjIyH4rf5SqM8Xxo0bN/DFF18gPDxcSGvWrBkiIiLg6OgIJSUlfPPNN3B3d8eBAweEdUg5OTkvrMfV1RX/+c9/YGJigps3b2LBggUYNmwYkpOToaysXKc+vsyxKi0tRWlpqfC+sLCwTnURERERvYytW7eiW7du6NOnT43by8vLMXbsWMhkMmzYsOE1t47ozdfkhuXS09NRWlqKwYMH1yn/unXrYGNjA319fTRr1gybNm2q1zqV9PR0SKVS0XphS0tL0bSby5cvo7i4GC1btkSzZs2E161bt3Dz5k1kZWWJ0kNDQ4WyHR0dRfU5Ojri+vXrqKioENLs7e1Feezt7ZGenl7nPnz44YeIjY2FtbU15s6dizNnzgjbhg0bJrSrS5cuAKpmElhZWeG///1vjeXV1p+nrVy5ErGxsfj222+hrq5e57Y+7c6dO3B1dcWYMWMwadIkIb1Vq1YICAiAnZ0devfujZUrV+K///0vVq9eXa/y33//fYwYMQLdunWDu7s7Dh06hAsXLgjT8uviRceqJitWrICOjo7wateuXb3aTURERP8urVq1grKyMnJzc0Xpubm5MDAweO6+JSUliI2Nha+vb43bqwPu27dvIyEhgaPcRArQ5Ea6NTQ06pw3NjYWs2fPRkREBOzt7dG8eXOsXr0a586dE/IoKSlBJpOJ9isvL69Xm4qLi2FoaFhjsKarqwtdXV3Rmuuapkq/rOrpzE/34dn2Dxs2DLdv30Z8fDwSEhIwePBg+Pv7Izw8HFu2bMHff/8NAMKa6BMnTuCXX37Bvn37RGW3atUKCxcuRGBg4HP7Ex4ejpUrV+L48eOiG4tVfynk5ubC0NBQSM/NzYW1tbWojOzsbAwcOBAODg7YtGnTC4+DnZ2daMq9gYFBvb+YOnbsiFatWuHGjRt1vqjzomP19EyLavPnz0dAQIDwvrCwkIE3ERER1UpVVRU2NjZITEyEu7s7AAj3zZk+ffpz942Li0NpaWmNAwTVAff169dx8uRJtGzZUhHNJ/rXa3JBt7m5OTQ0NJCYmPjcdSkAcPr0aTg4OGDatGlC2s2bN0V59PX1cffuXeF9RUUFrly5goEDBwKoGtV+8uQJUlJShOnlGRkZokdC9erVCzk5OZBKpbVO3TYzM5NLs7KywunTp+Xa3KlTJ9H05mcfhXX27Flheru+vj4A4O7du+jZsycA1Piccn19fXh5ecHLywv9+/fHnDlzEB4ejrZt28rl/eabb4RAHAAuXLiAiRMn4qeffoKpqSmkUmmN/QGq7k6+fPlyHDt2TJjOXs3ExAQGBgZITEwUguzCwkKcO3dOdHfwO3fuYODAgbCxsUF0dHSd1kmnpaWJAnl7e3skJiaKbpKXkJAgN2vgaX/++ScePHggKudFXnSsaqKmpiYsQyAiIiKqi4CAAHh5ecHW1hZ9+vTBmjVrUFJSAh8fHwCAp6cn2rZtixUrVoj227p1K9zd3eUC6vLycowePRqpqak4dOgQKioqhGV4enp6UFVVfT0dI/oXaHJBt7q6OubNm4e5c+dCVVUVjo6OuHfvHn799Ve50Ulzc3Ps3LkTx44dg4mJCXbt2oULFy7AxMREyDNo0CAEBATg8OHDMDU1RWRkpCigtrCwgKurK6ZMmYINGzZAKpVi5syZohF3Z2dn2Nvbw93dHWFhYejUqROys7Nx+PBhjBo1Si74rPbJJ5+gd+/eCAkJwbhx45CcnIy1a9di/fr1onynT59GWFgY3N3dkZCQgLi4OBw+fBhA1ch/3759sXLlSpiYmCAvLw+LFi0S7R8UFAQbGxt06dIFpaWlOHTokGhN+rOeDRbv378PoOoiwfPuZrlq1SoEBQUhJiYGxsbGwgd39TR0iUSCmTNnYtmyZTA3N4eJiQkCAwNhZGQkXLW9c+cOnJyc0KFDB4SHh+PevXtC+dWj1Dt27ICqqqpwkWH//v3Ytm0btmzZIuSdMWMGBgwYgIiICAwfPhyxsbG4ePGiMGpeXFyMJUuW4L333oOBgQFu3ryJuXPnwszMDC4uLkI5WVlZePjwIbKyslBRUSFc0DAzM0OzZs1e+lgRERER1ce4ceNw7949BAUFIScnB9bW1jh69KhwD5usrCy5gYqMjAycOnUKP/zwg1x5d+7cEW5E++yMw5MnT8LJyUkh/SD6N2pyQTdQdTduqVSKoKAgZGdnw9DQEFOnTpXLN2XKFFy6dAnjxo2DRCKBh4cHpk2bhiNHjgh5Jk6ciMuXL8PT0xNSqRSzZs0SRrmrRUdHw8/PDwMGDECbNm2wbNky4eZnACCRSBAfH4+FCxfCx8cH9+7dg4GBAd5+++0a76perVevXti7dy+CgoIQEhICQ0NDLF26VHQTNaAqOL948SKWLFkCbW1tREZGigLDbdu2wdfXFzY2NrCwsEBYWBiGDh0qbFdVVcX8+fORmZkJDQ0N9O/fH7GxsXU+3nW1YcMGlJWVYfTo0aL04OBgLF68GAAwd+5clJSUYPLkycjPz0e/fv1w9OhRYd13QkICbty4gRs3buCtt94SlfP0FPqQkBDcvn0bUqkUlpaW2LNnj6heBwcHxMTEYNGiRViwYAHMzc1x4MABdO3aFQCgrKyMn3/+GTt27EB+fj6MjIwwdOhQhISEiEahg4KCsGPHDuF9daDPLyMiIiJ63aZPn17rdPKaljlaWFjILaOsZmxsXOs2Inq1JDL+b2vUjI2NMXPmTLlnidObo7CwEDo6OugzbCykKpzKRURE9G9z+rtdDd0Eokar+rdyQUFBk73RX5O7ezkRERERERFRU8Ggm4iIiIiIiEhBmuSa7n+TzMzMhm4CERERERERvSSOdBMREREREREpCINuIiIiIiIiIgXh9HKiRiIhdnOTvSMjERERERHVjCPdRERERERERArCoJuIiIiIiIhIQRh0ExERERERESkIg24iIiIiIiIiBWHQTURERERERKQgvHs5USMx2P19SKUqDd0MIiIiekbyD981dBOIqAnjSDcRERERERGRgjDoJiIiIiIiIlIQBt1ERERERERECsKgm4iIiIiIiEhBGHQTERERERERKQiDbiIiIiKiV2DdunUwNjaGuro67OzscP78+efmz8/Ph7+/PwwNDaGmpoZOnTohPj5e2F5RUYHAwECYmJhAQ0MDpqamCAkJgUwmU3RXiOgVapRBd2ZmJiQSCdLS0hRel7GxMdasWaPweoiIiIjozbVnzx4EBAQgODgYqamp6NGjB1xcXJCXl1dj/rKyMgwZMgSZmZnYt28fMjIysHnzZrRt21bIs2rVKmzYsAFr165Feno6Vq1ahbCwMHzxxRevq1tE9Ao0yqCbFEMikeDAgQP12ic2NhYSiQTu7u7Pzffw4UN89NFHsLCwgIaGBtq3b4+PP/4YBQUFonxZWVkYPnw4NDU10bp1a8yZMwdPnjwRtu/fvx9DhgyBvr4+tLW1YW9vj2PHjonKWLx4MSQSiehlaWkpyvP48WP4+/ujZcuWaNasGd577z3k5ubKHY9nX7GxscL2u3fv4oMPPkCnTp2gpKSEmTNnvpJjRURERG+eyMhITJo0CT4+PujcuTM2btwITU1NbNu2rcb827Ztw8OHD3HgwAE4OjrC2NgYAwYMQI8ePYQ8Z86cwciRIzF8+HAYGxtj9OjRGDp06AtH0ImocWHQTbXKzMzE7Nmz0b9//xfmzc7ORnZ2NsLDw3HlyhVs374dR48eha+vr5CnoqICw4cPR1lZGc6cOYMdO3Zg+/btCAoKEvL8+OOPGDJkCOLj45GSkoKBAwfCzc0Nly5dEtXXpUsX3L17V3idOnVKtH3WrFn4/vvvERcXh//973/Izs7Gf/7zH7l2R0dHi8p5OmAuLS2Fvr4+Fi1aJPoC/KfHioiIiN4sZWVlSElJgbOzs5CmpKQEZ2dnJCcn17jPwYMHYW9vD39/f7Rp0wZdu3ZFaGgoKioqhDwODg5ITEzEtWvXAACXL1/GqVOnMGzYMMV2iIheqQYNuisrKxEWFgYzMzOoqamhffv2WL58uVy+iooK+Pr6CutZLCwsEBUVJcrj5OQkNxLp7u4Ob29v4X1eXh7c3NygoaEBExMT7N69W66u/Px8+Pn5CSOtgwYNwuXLl5/bj6SkJPTp0wdaWlrQ1dWFo6Mjbt++LWzfsGEDTE1NoaqqCgsLC+zatUu0v0QiwZYtWzBq1ChoamrC3NwcBw8eFJUvkUiQmJgIW1tbaGpqwsHBARkZGaJyvvvuO/Tq1Qvq6uro2LEjlixZIowiGxsbAwBGjRoFiUQivK9NRUUFxo8fjyVLlqBjx47PzQsAXbt2xTfffAM3NzeYmppi0KBBWL58Ob7//nuhDT/88AOuXr2Kr776CtbW1hg2bBhCQkKwbt06lJWVAQDWrFmDuXPnonfv3jA3N0doaCjMzc3x/fffi+qTSqUwMDAQXq1atRK2FRQUYOvWrYiMjMSgQYNgY2OD6OhonDlzBmfPnhWVo6urKypHXV1d2GZsbIyoqCh4enpCR0fnlR0rIiIierPcv38fFRUVaNOmjSi9TZs2yMnJqXGf33//Hfv27UNFRQXi4+MRGBiIiIgILFu2TMjz6aef4v3334elpSVUVFTQs2dPzJw5E+PHj1dof4jo1WrQoHv+/PlYuXIlAgMDcfXqVcTExMh9WAFVwflbb72FuLg4XL16FUFBQViwYAH27t1br/q8vb3xxx9/4OTJk9i3bx/Wr18vt85mzJgxyMvLw5EjR5CSkoJevXph8ODBePjwYY1lPnnyBO7u7hgwYAB+/vlnJCcnY/LkyZBIJACAb7/9FjNmzMAnn3yCK1euYMqUKfDx8cHJkydF5SxZsgRjx47Fzz//jHfeeQfjx4+Xq3PhwoWIiIjAxYsXIZVKMXHiRGHbTz/9BE9PT8yYMQNXr17Fl19+ie3btwsXMS5cuADg/0d2q9/XZunSpWjdurVopLq+CgoKoK2tDalUCgBITk5Gt27dRH9jFxcXFBYW4tdff62xjMrKShQVFUFPT0+Ufv36dRgZGaFjx44YP348srKyhG0pKSkoLy8XXW22tLRE+/bt5a42+/v7o1WrVujTpw+2bdv2Ujcmqe+xKi0tRWFhoehFRERE/y6VlZVo3bo1Nm3aBBsbG4wbNw4LFy7Exo0bhTx79+7F7t27ERMTg9TUVOzYsQPh4eHYsWNHA7aciOpL2lAVFxUVISoqCmvXroWXlxcAwNTUFP369UNmZqYor4qKCpYsWSK8NzExQXJyMvbu3YuxY8fWqb5r167hyJEjOH/+PHr37g0A2Lp1K6ysrIQ8p06dwvnz55GXlwc1NTUAQHh4OA4cOIB9+/Zh8uTJcuUWFhaioKAA7777LkxNTQFAVGZ4eDi8vb0xbdo0AEBAQADOnj2L8PBwDBw4UMjn7e0NDw8PAEBoaCg+//xznD9/Hq6urkKe5cuXY8CAAQCqrnwOHz4cjx8/hrq6OpYsWYJPP/1UOJYdO3ZESEgI5s6di+DgYOjr6wP4/5Hd5zl16hS2bt36j25kd//+fYSEhIiOWU5OTo1XgKu31SQ8PBzFxcWiv7OdnR22b98OCwsL3L17F0uWLEH//v1x5coVNG/eHDk5OVBVVYWurq5cXU/Xs3TpUgwaNAiampr44YcfMG3aNBQXF+Pjjz+ucz9f5litWLFCdD4TERFR09aqVSsoKyvL3T8mNze31t9dhoaGUFFRgbKyspBmZWWFnJwclJWVQVVVFXPmzBFGuwGgW7duuH37NlasWCH85iOixq/BRrrT09NRWlqKwYMH1yn/unXrYGNjA319fTRr1gybNm0SjW7WpT6pVAobGxshzdLSUhSYXb58GcXFxcLNt6pft27dws2bN5GVlSVKDw0NhZ6eHry9veHi4gI3NzdERUXh7t27onodHR1FbXF0dER6eroorXv37sK/tbS0oK2tLTcK/3QeQ0NDABDyXL58GUuXLhW1b9KkSbh79y4ePXpU4zGpqT9FRUWYMGECNm/eLJqy/bTQ0FDRfs/+HQoLCzF8+HB07twZixcvrrGMuoiJicGSJUuwd+9etG7dWkgfNmwYxowZg+7du8PFxQXx8fHIz8+v98yHwMBAODo6omfPnpg3bx7mzp2L1atX13n/uhyrmsyfPx8FBQXC648//qhXu4mIiKhxUVVVhY2NDRITE4W0yspKJCYmwt7evsZ9HB0dcePGDVRWVgpp165dg6GhIVRVVQEAjx49gpKS+Oe6srKyaB8iavwabKRbQ0OjznljY2Mxe/ZsREREwN7eHs2bN8fq1atx7tw5IY+SkpLc1ODy8vJ6tam4uBiGhoZISkqS26arqwtdXV3RiGb1lOfo6Gh8/PHHOHr0KPbs2YNFixYhISEBffv2rXPdKioqovcSiUTuA/XpPNXT16vzFBcXY8mSJTXeLOzpdcpPMzIykuvPzZs3kZmZCTc3NyG9ug6pVIqMjAxMnTpVNPJsZGQk/LuoqAiurq5o3rw5vv32W1GbDQwM5O62WX1F+NmrwLGxsfDz80NcXJxomnhNdHV10alTJ9y4cUMoq6ysDPn5+aKLKs+72gxUjaCHhISgtLRUmOnwPHU5VtWzH56mpqZWp/KJiIio6QgICICXlxdsbW3Rp08frFmzBiUlJfDx8QEAeHp6om3btlixYgUA4MMPP8TatWsxY8YMfPTRR7h+/TpCQ0NFM+7c3NywfPlytG/fHl26dMGlS5cQGRkpWmJIRI1fgwXd5ubm0NDQQGJiIvz8/J6b9/Tp03BwcBCmaANVAc/T9PX1RSPMFRUVuHLlijCF29LSEk+ePEFKSoowvTwjIwP5+fnCPr169UJOTg6kUmmtNxozMzOrMb1nz57o2bMn5s+fD3t7e8TExKBv376wsrLC6dOnRVOATp8+jc6dOz+3z/XVq1cvZGRk1No+oCpof/qOmFKpVC6/pqYmfvnlF1HaokWLhOUA7dq1g6qqqtwaa6BqhNvFxQVqamo4ePCgXLBvb2+P5cuXIy8vTxi5TkhIgLa2tuh4fP3115g4cSJiY2MxfPjwF/a9uLgYN2/exIQJEwAANjY2UFFRQWJiIt577z0AVX/rrKysWq82A0BaWhpatGhR54DY0tLyhceKiIiI/h3GjRuHe/fuISgoCDk5ObC2tsbRo0eFpXRZWVmiUet27drh2LFjmDVrFrp37462bdtixowZmDdvnpDniy++QGBgIKZNm4a8vDwYGRlhypQpoie/EFHj12BBt7q6ujClV1VVFY6Ojrh37x5+/fVXuSnn5ubm2LlzJ44dOwYTExPs2rULFy5cgImJiZBn0KBBCAgIwOHDh2FqaorIyEhRQG1hYQFXV1dMmTIFGzZsgFQqxcyZM0Uj7s7OzrC3t4e7uzvCwsLQqVMnZGdn4/Dhwxg1ahRsbW3l+nHr1i1s2rQJI0aMgJGRETIyMnD9+nV4enoCAObMmYOxY8eiZ8+ecHZ2xvfff4/9+/fj+PHjr/R4BgUF4d1330X79u0xevRoKCkp4fLly7hy5YpwF0xjY2MkJibC0dERampqaNGihVw56urq6Nq1qyiterT42fSnFRYWYujQoXj06BG++uor0Q3C9PX1oaysjKFDh6Jz586YMGECwsLCkJOTg0WLFsHf318IdGNiYuDl5YWoqCjY2dkJa7A1NDSEO4jPnj0bbm5u6NChA7KzsxEcHAxlZWVhTbyOjg58fX0REBAAPT09aGtr46OPPoK9vb0w++D7779Hbm4u+vbtC3V1dSQkJCA0NBSzZ88W9at6JkBxcTHu3buHtLQ0qKqqonPnzi99rIiIiOjNNH36dEyfPr3GbTXNpLS3t5d7ssrTmjdvjjVr1mDNmjWvqIVE1BAaLOgGqtbUSqVSBAUFITs7G4aGhpg6dapcvilTpuDSpUsYN24cJBIJPDw8MG3aNBw5ckTIM3HiRFy+fBmenp6QSqWYNWuW6EZlQNU0cD8/PwwYMABt2rTBsmXLEBgYKGyXSCSIj4/HwoUL4ePjg3v37sHAwABvv/12jXdVB6pGhn/77Tfs2LEDDx48gKGhIfz9/TFlyhQAVY8ti4qKQnh4OGbMmAETExNER0fDycnpFRzB/+fi4oJDhw5h6dKlWLVqFVRUVGBpaSmaRRAREYGAgABs3rwZbdu2lbth3T+RmpoqTPd/dvT81q1bMDY2hrKyMg4dOoQPP/wQ9vb20NLSgpeXF5YuXSrk3bRpE548eQJ/f3/4+/sL6V5eXti+fTsA4M8//4SHhwcePHgAfX199OvXD2fPnhVuFgcAn332GZSUlPDee++htLQULi4uWL9+vbBdRUUF69atw6xZsyCTyWBmZobIyEhMmjRJ1PaePXsK/05JSUFMTAw6dOjwSo8dERERERG9uSSyl3lGEhG9MoWFhdDR0YHtwGGQSlVevAMRERG9Vsk/fNfQTSD616r+rVz9OOKmqEGf001ERERERET0JmPQTURERERERKQgDLqJiIiIiIiIFIRBNxEREREREZGCMOgmIiIiIiIiUpAGfWQYEf2/xAOxTfaOjEREREREVDOOdBMREREREREpCINuIiIiIiIiIgVh0E1ERERERESkIAy6iYiIiIiIiBSEQTcRERERERGRgvDu5USNxECXd6Es5X9JIiKiujr/04mGbgIR0QtxpJuIiIiIiIhIQRh0ExERERERESkIg24iIiIiIiIiBWHQTURERERERKQgDLqJiIiIiIiIFKRJB92ZmZmQSCRIS0tTeF3GxsZYs2aNwuupiUQiwYEDB/5RGd7e3nB3dxfeOzk5YebMmf+oTCIiIqKmYN26dTA2Noa6ujrs7Oxw/vz55+bPz8+Hv78/DA0Noaamhk6dOiE+Pl7YvnjxYkgkEtHL0tJS0d0goiaqSQfdTc3+/ftha2sLXV1daGlpwdraGrt27XotdUdFRWH79u0KrSMpKQkjR46EoaGh0L/du3fL5YuLi4OlpSXU1dXRrVs30ZdYeXk55s2bh27dukFLSwtGRkbw9PREdnZ2jXWWlpbC2tq6xosvP//8M/r37w91dXW0a9cOYWFhou11+XvIZDIEBQXB0NAQGhoacHZ2xvXr10V9fvZLt/p14cKF+h5CIiIiesX27NmDgIAABAcHIzU1FT169ICLiwvy8vJqzF9WVoYhQ4YgMzMT+/btQ0ZGBjZv3oy2bduK8nXp0gV3794VXqdOnXod3SGiJohB92ukp6eHhQsXIjk5GT///DN8fHzg4+ODY8eOKbxuHR0d6OrqKrSOM2fOoHv37vjmm2+E/nl6euLQoUOiPB4eHvD19cWlS5fg7u4Od3d3XLlyBQDw6NEjpKamIjAwEKmpqdi/fz8yMjIwYsSIGuucO3cujIyM5NILCwsxdOhQdOjQASkpKVi9ejUWL16MTZs2CXnq8vcICwvD559/jo0bN+LcuXPQ0tKCi4sLHj9+DABwcHAQfeHevXsXfn5+MDExga2t7Ss5rkRERPTyIiMjMWnSJPj4+KBz587YuHEjNDU1sW3bthrzb9u2DQ8fPsSBAwfg6OgIY2NjDBgwAD169BDlk0qlMDAwEF6tWrV6Hd0hoiaoSQTdlZWVCAsLg5mZGdTU1NC+fXssX75cLl9FRQV8fX1hYmICDQ0NWFhYICoqSpSnpmnV7u7u8Pb2Ft7n5eXBzc0NGhoaMDExqXG0Nj8/H35+ftDX14e2tjYGDRqEy5cvP7cfTk5OGDVqFKysrGBqaooZM2age/fudboyev/+fYwaNQqampowNzfHwYMH69XvZ6eXP+vw4cPQ0dHB7t27a5y2n5+fD4lEgqSkpFrLWLBgAUJCQuDg4CD0z9XVFfv37xfyREVFwdXVFXPmzIGVlRVCQkLQq1cvrF27FkDVxYGEhASMHTsWFhYW6Nu3L9auXYuUlBRkZWWJ6jty5Ah++OEHhIeHy7Vl9+7dKCsrw7Zt29ClSxe8//77+PjjjxEZGSnkedHfQyaTYc2aNVi0aBFGjhyJ7t27Y+fOncjOzham+6uqqoq+cFu2bInvvvsOPj4+kEgktR4rIiIiUryysjKkpKTA2dlZSFNSUoKzszOSk5Nr3OfgwYOwt7eHv78/2rRpg65duyI0NBQVFRWifNevX4eRkRE6duyI8ePHy/1OISKq1iSC7vnz52PlypUIDAzE1atXERMTgzZt2sjlq6ysxFtvvYW4uDhcvXoVQUFBWLBgAfbu3Vuv+ry9vfHHH3/g5MmT2LdvH9avXy83BWnMmDHIy8vDkSNHkJKSgl69emHw4MF4+PBhneqQyWRITExERkYG3n777RfmX7JkCcaOHYuff/4Z77zzDsaPHy/U9U/7HRMTAw8PD+zevRvjx4+v0z51VVBQAD09PeF9cnKy6IsPAFxcXGr94qsuQyKRiEbqc3NzMWnSJOzatQuamppy+yQnJ+Ptt9+GqqqqqJ6MjAz89ddfcvlr+nvcunULOTk5ovbq6OjAzs7uuV/UDx48gI+PT639ISIiotfj/v37qKiokPvd2KZNG+Tk5NS4z++//459+/ahoqIC8fHxCAwMREREBJYtWybksbOzw/bt23H06FFs2LABt27dQv/+/VFUVKTQ/hBR0yRt6Aa8SFFREaKiorB27Vp4eXkBAExNTdGvXz9kZmaK8qqoqGDJkiXCexMTEyQnJ2Pv3r0YO3Zsneq7du0ajhw5gvPnz6N3794AgK1bt8LKykrIc+rUKZw/fx55eXlQU1MDAISHh+PAgQPYt28fJk+eXGv5BQUFaNu2LUpLS6GsrIz169djyJAhL2yXt7c3PDw8AAChoaH4/PPPcf78ebi6uv6jfq9btw4LFy7E999/jwEDBrywHfWxd+9eXLhwAV9++aWQlpOTU68vvsePH2PevHnw8PCAtrY2gKoA2dvbG1OnToWtra3ceVBdj4mJiVw91dtatGgB4Pl/j+o21ae9W7duhYuLC956660atwNV69BLS0uF94WFhbXmJSIiotersrISrVu3xqZNm6CsrAwbGxvcuXMHq1evRnBwMABg2LBhQv7u3bvDzs4OHTp0wN69e+Hr69tQTSeiRqrRB93p6ekoLS3F4MGD65R/3bp12LZtG7KysvD333+jrKwM1tbW9apPKpXCxsZGSLO0tBSNsl6+fBnFxcVo2bKlaN+///4bN2/eRFZWFjp37iykL1iwAAsWLAAANG/eHGlpaSguLkZiYiICAgLQsWNHODk5ITQ0FKGhocJ+V69eRfv27QFUfaBX09LSgra2tmj0/WX6vW/fPuTl5eH06dPCBYa66tKlC27fvg0A6N+/P44cOSLafvLkSfj4+GDz5s3o0qVLvcquVl5ejrFjx0Imk2HDhg1C+hdffIGioiLMnz//pcp92vP+HvX1559/4tixYy+cYbBixQrRRRIiIiJSjFatWkFZWRm5ubmi9NzcXBgYGNS4j6GhIVRUVKCsrCykWVlZIScnB2VlZaJZdNV0dXXRqVMn3Lhx49V2gIjeCI0+6NbQ0Khz3tjYWMyePRsRERGwt7dH8+bNsXr1apw7d07Io6SkBJlMJtqvvLy8Xm0qLi6GoaFhjeubdXV1oaurK1oP/fT0aiUlJZiZmQEArK2tkZ6ejhUrVsDJyQlTp04VjUw/fYMwFRUVUT0SiQSVlZV17ndNevbsidTUVGzbtg22trbCGmQlpapVB08fp2ePUXx8vJD27N/of//7H9zc3PDZZ5/B09NTtM3AwKBOX3zVAfft27dx4sQJYZQbAE6cOIHk5GRhlkE1W1tbjB8/Hjt27Ki1nuo2VHve36M6X25uLgwNDUXl1HRBIzo6Gi1btqz1pm/V5s+fj4CAAOF9YWEh2rVr99x9iIiIqP5UVVVhY2ODxMRE4d42lZWVSExMxPTp02vcx9HRETExMaisrBR+E127dg2GhoY1BtxA1W/DmzdvYsKECQrpBxE1bY1+Tbe5uTk0NDSQmJj4wrynT5+Gg4MDpk2bhp49e8LMzAw3b94U5dHX18fdu3eF9xUVFcKds4GqUe0nT54gJSVFSMvIyEB+fr7wvlevXsjJyYFUKoWZmZno1apVK7n0p4PuZ1VWVgpTjfX09ET7SaV1uyZSl37XxNTUFCdPnsR3332Hjz76SHSMAIiO07OP4+rQoYPQzqcfoZGUlIThw4dj1apVNU6zt7e3l/tbJiQkwN7eXnhfHXBfv34dx48fl5tR8Pnnn+Py5ctIS0tDWlqa8MixPXv2CDfYs7e3x48//ii6WJCQkAALCwthanlNnv57mJiYwMDAQNTewsJCnDt3TtReoOoCRXR0NDw9PeUukDxLTU0N2traohcREREpRkBAADZv3owdO3YgPT0dH374IUpKSoT7r3h6eopmz3344Yd4+PAhZsyYgWvXruHw4cMIDQ2Fv7+/kGf27Nn43//+h8zMTJw5cwajRo2CsrKysBSQiOhpjX6kW11dHfPmzcPcuXOhqqoKR0dH3Lt3D7/++qvclHNzc3Ps3LkTx44dg4mJCXbt2oULFy6I1vYOGjQIAQEBOHz4MExNTREZGSkKqC0sLODq6oopU6Zgw4YNkEqlmDlzpmg019nZGfb29nB3d0dYWBg6deqE7OxsHD58GKNGjar1UVErVqyAra0tTE1NUVpaivj4eOzatUs0dfpl1KXftenUqRNOnjwJJycnSKVSrFmzBhoaGujbty9WrlwJExMT5OXlYdGiRS8s6+TJk3j33XcxY8YMvPfee8K6Z1VVVeHCw4wZMzBgwABERERg+PDhiI2NxcWLF4VHeZWXl2P06NFITU3FoUOHUFFRIZSjp6cHVVVVYcp9tWbNmgGouohQvZb6gw8+wJIlS+Dr64t58+bhypUriIqKwmeffSbs96K/h0QiwcyZM7Fs2TKYm5vDxMQEgYGBMDIykrsT/IkTJ3Dr1i34+fm98DgRERHR6zNu3Djcu3cPQUFByMnJgbW1NY4ePSrcsyUrK0sY0QaAdu3a4dixY5g1axa6d++Otm3bYsaMGZg3b56Q588//4SHhwcePHgAfX199OvXD2fPnhUGLoiIntbog24ACAwMhFQqRVBQELKzs2FoaIipU6fK5ZsyZQouXbqEcePGQSKRwMPDA9OmTROtN544cSIuX74MT09PSKVSzJo1CwMHDhSVEx0dDT8/PwwYMABt2rTBsmXLEBgYKGyXSCSIj4/HwoUL4ePjg3v37sHAwABvv/12jXdVr1ZSUoJp06bhzz//hIaGBiwtLfHVV19h3Lhx/+j41KXfz2NhYYETJ07AyckJysrKiIiIwLZt2+Dr6wsbGxtYWFggLCwMQ4cOfW45O3bswKNHj7BixQqsWLFCSB8wYIAwFd/BwQExMTFYtGgRFixYAHNzcxw4cABdu3YFANy5c0d4HNqzU7irLw7UhY6ODn744Qf4+/vDxsYGrVq1QlBQkGj0vS5/j7lz56KkpASTJ09Gfn4++vXrh6NHj0JdXV1U39atW+Hg4ABLS8s6tY+IiIhen+nTp9c6nbym5YL29vY4e/ZsreXFxsa+qqYR0b+ARPbsAmcieq0KCwuho6ODXn37Q7mOSwqIiIgIOP/TiYZuAhEpWPVv5YKCgia7LLPRr+kmIiIiIiIiaqoYdBMREREREREpCINuIiIiIiIiIgVh0E1ERERERESkIAy6iYiIiIiIiBSEQTcRERERERGRgvD5RESNxMljh5rsYxCIiIiIiKhmHOkmIiIiIiIiUhCOdBM1MJlMBgAoLCxs4JYQERERETUu1b+Rq38zN0UMuoka2IMHDwAA7dq1a+CWEBERERE1Tg8ePICOjk5DN+OlMOgmamB6enoAgKysrCb7QUINo7CwEO3atcMff/zB+wFQvfDcoZfFc4deFs8delkFBQVo37698Ju5KWLQTdTAlJSqbq2go6PDLyF6Kdra2jx36KXw3KGXxXOHXhbPHXpZ1b+Zm6Km23IiIiIiIiKiRo5BNxEREREREZGCMOgmamBqamoIDg6GmppaQzeFmhieO/SyeO7Qy+K5Qy+L5w69rDfh3JHImvK914mIiIiIiIgaMY50ExERERERESkIg24iIiIiIiIiBWHQTURERERERKQgDLqJXoN169bB2NgY6urqsLOzw/nz55+bPy4uDpaWllBXV0e3bt0QHx//mlpKjU19zp3Nmzejf//+aNGiBVq0aAFnZ+cXnmv05qrv50612NhYSCQSuLu7K7aB1GjV99zJz8+Hv78/DA0Noaamhk6dOvF761+qvufOmjVrYGFhAQ0NDbRr1w6zZs3C48ePX1NrqbH48ccf4ebmBiMjI0gkEhw4cOCF+yQlJaFXr15QU1ODmZkZtm/frvB2/hMMuokUbM+ePQgICEBwcDBSU1PRo0cPuLi4IC8vr8b8Z86cgYeHB3x9fXHp0iW4u7vD3d0dV65cec0tp4ZW33MnKSkJHh4eOHnyJJKTk9GuXTsMHToUd+7cec0tp4ZW33OnWmZmJmbPno3+/fu/ppZSY1Pfc6esrAxDhgxBZmYm9u3bh4yMDGzevBlt27Z9zS2nhlbfcycmJgaffvopgoODkZ6ejq1bt2LPnj1YsGDBa245NbSSkhL06NED69atq1P+W7duYfjw4Rg4cCDS0tIwc+ZM+Pn54dixYwpu6T8gIyKF6tOnj8zf3194X1FRITMyMpKtWLGixvxjx46VDR8+XJRmZ2cnmzJlikLbSY1Pfc+dZz158kTWvHlz2Y4dOxTVRGqkXubcefLkiczBwUG2ZcsWmZeXl2zkyJGvoaXU2NT33NmwYYOsY8eOsrKystfVRGqk6nvu+Pv7ywYNGiRKCwgIkDk6Oiq0ndS4AZB9++23z80zd+5cWZcuXURp48aNk7m4uCiwZf8MR7qJFKisrAwpKSlwdnYW0pSUlODs7Izk5OQa90lOThblBwAXF5da89Ob6WXOnWc9evQI5eXl0NPTU1QzqRF62XNn6dKlaN26NXx9fV9HM6kReplz5+DBg7C3t4e/vz/atGmDrl27IjQ0FBUVFa+r2dQIvMy54+DggJSUFGEK+u+//474+Hi88847r6XN1HQ1xd/K0oZuANGb7P79+6ioqECbNm1E6W3atMFvv/1W4z45OTk15s/JyVFYO6nxeZlz51nz5s2DkZGR3BcTvdle5tw5deoUtm7dirS0tNfQQmqsXubc+f3333HixAmMHz8e8fHxuHHjBqZNm4by8nIEBwe/jmZTI/Ay584HH3yA+/fvo1+/fpDJZHjy5AmmTp3K6eX0QrX9Vi4sLMTff/8NDQ2NBmpZ7TjSTUT0Blq5ciViY2Px7bffQl1dvaGbQ41YUVERJkyYgM2bN6NVq1YN3RxqYiorK9G6dWts2rQJNjY2GDduHBYuXIiNGzc2dNOokUtKSkJoaCjWr1+P1NRU7N+/H4cPH0ZISEhDN43oleNIN5ECtWrVCsrKysjNzRWl5+bmwsDAoMZ9DAwM6pWf3kwvc+5UCw8Px8qVK3H8+HF0795dkc2kRqi+587NmzeRmZkJNzc3Ia2yshIAIJVKkZGRAVNTU8U2mhqFl/ncMTQ0hIqKCpSVlYU0Kysr5OTkoKysDKqqqgptMzUOL3PuBAYGYsKECfDz8wMAdOvWDSUlJZg8eTIWLlwIJSWODVLNavutrK2t3ShHuQGOdBMplKqqKmxsbJCYmCikVVZWIjExEfb29jXuY29vL8oPAAkJCbXmpzfTy5w7ABAWFoaQkBAcPXoUtra2r6Op1MjU99yxtLTEL7/8grS0NOE1YsQI4a6w7dq1e53Npwb0Mp87jo6OuHHjhnChBgCuXbsGQ0NDBtz/Ii9z7jx69EgusK6+eCOTyRTXWGrymuRv5Ya+kxvRmy42NlampqYm2759u+zq1auyyZMny3R1dWU5OTkymUwmmzBhguzTTz8V8p8+fVomlUpl4eHhsvT0dFlwcLBMRUVF9ssvvzRUF6iB1PfcWblypUxVVVW2b98+2d27d4VXUVFRQ3WBGkh9z51n8e7l/171PXeysrJkzZs3l02fPl2WkZEhO3TokKx169ayZcuWNVQXqIHU99wJDg6WNW/eXPb111/Lfv/9d9kPP/wgMzU1lY0dO7ahukANpKioSHbp0iXZpUuXZABkkZGRskuXLslu374tk8lksk8//VQ2YcIEIf/vv/8u09TUlM2ZM0eWnp4uW7dunUxZWVl29OjRhurCCzHoJnoNvvjiC1n79u1lqqqqsj59+sjOnj0rbBswYIDMy8tLlH/v3r2yTp06yVRVVWVdunSRHT58+DW3mBqL+pw7HTp0kAGQewUHB7/+hlODq+/nztMYdP+71ffcOXPmjMzOzk6mpqYm69ixo2z58uWyJ0+evOZWU2NQn3OnvLxctnjxYpmpqalMXV1d1q5dO9m0adNkf/311+tvODWokydP1vj7pfp88fLykg0YMEBuH2tra5mqqqqsY8eOsujo6Nfe7vqQyGScv0FERERERESkCFzTTURERERERKQgDLqJiIiIiIiIFIRBNxEREREREZGCMOgmIiIiIiIiUhAG3UREREREREQKwqCbiIiIiIiISEEYdBMREREREREpCINuIiIiIiIiIgVh0E1ERERERESkIAy6iYiIqFHz9vaGRCKRe924cQMA8OOPP8LNzQ1GRkaQSCQ4cODAC8usqKjAypUrYWlpCQ0NDejp6cHOzg5btmxRcG+IiOjfRtrQDSAiIiJ6EVdXV0RHR4vS9PX1AQAlJSXo0aMHJk6ciP/85z91Km/JkiX48ssvsXbtWtja2qKwsBAXL17EX3/99crbXq2srAyqqqoKK5+IiBonjnQTERFRo6empgYDAwPRS1lZGQAwbNgwLFu2DKNGjapzeQcPHsS0adMwZswYmJiYoEePHvD19cXs2bOFPJWVlQgLC4OZmRnU1NTQvn17LF++XNj+yy+/YNCgQdDQ0EDLli0xefJkFBcXC9u9vb3h7u6O5cuXw8jICBYWFgCAP/74A2PHjoWuri709PQwcuRIZGZm/sMjREREjRWDbiIiIvrXMTAwwIkTJ3Dv3r1a88yfPx8rV65EYGAgrl69ipiYGLRp0wZA1ei6i4sLWrRogQsXLiAuLg7Hjx/H9OnTRWUkJiYiIyMDCQkJOHToEMrLy+Hi4oLmzZvjp59+wunTp9GsWTO4urqirKxMoX0mIqKGwenlRERE1OgdOnQIzZo1E94PGzYMcXFxL11eZGQkRo8eDQMDA3Tp0gUODg4YOXIkhg0bBgAoKipCVFQU1q5dCy8vLwCAqakp+vXrBwCIiYnB48ePsXPnTmhpaQEA1q5dCzc3N6xatUoIzrW0tLBlyxZhWvlXX32FyspKbNmyBRKJBAAQHR0NXV1dJCUlYejQoS/dJyIiapwYdBMREVGjN3DgQGzYsEF4Xx3ovqzOnTvjypUrSElJwenTp4WbsXl7e2PLli1IT09HaWkpBg8eXOP+6enp6NGjh6gdjo6OqKysREZGhhB0d+vWTbSO+/Lly7hx4waaN28uKu/x48e4efPmP+oTERE1Tgy6iYiIqNHT0tKCmZnZKy1TSUkJvXv3Ru/evTFz5kx89dVXmDBhAhYuXAgNDY1XUsezFweKi4thY2OD3bt3y+WtvjEcERG9Wbimm4iIiAhVo99A1Xptc3NzaGhoIDExsca8VlZWuHz5MkpKSoS006dPQ0lJSbhhWk169eqF69evo3Xr1jAzMxO9dHR0Xm2HiIioUWDQTURERE1acXEx0tLSkJaWBgC4desW0tLSkJWVVes+o0ePxmeffYZz587h9u3bSEpKgr+/Pzp16gRLS0uoq6tj3rx5mDt3Lnbu3ImbN2/i7Nmz2Lp1KwBg/PjxUFdXh5eXF65cuYKTJ0/io48+woQJE4Sp5TUZP348WrVqhZEjR+Knn37CrVu3kJSUhI8//hh//vnnKz0uRETUODDoJiIioibt4sWL6NmzJ3r27AkACAgIQM+ePREUFFTrPi4uLvj+++/h5uaGTp06wcvLC5aWlvjhhx8glVatvgsMDMQnn3yCoKAgWFlZYdy4ccjLywMAaGpq4tixY3j48CF69+6N0aNHY/DgwVi7du1z26qpqYkff/wR7du3x3/+8x9YWVnB19cXjx8/hra29is6IkRE1JhIZDKZrKEbQURERERERPQm4kg3ERERERERkYIw6CYiIiIiIiJSEAbdRERERERERArCoJuIiIiIiIhIQRh0ExERERERESkIg24iIiIiIiIiBWHQTURERERERKQgDLqJiIiIiIiIFIRBNxEREREREZGCMOgmIiIiIiIiUhAG3UREREREREQKwqCbiIiIiIiISEH+D5vTufc5lKNiAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "from sklearn.metrics import accuracy_score, f1_score, precision_score, recall_score\n",
    "\n",
    "# Combine results and save\n",
    "df_all_models = pd.concat(all_results, ignore_index=True)\n",
    "df_all_models.to_csv(\"judge_results_all_models.csv\", index=False)\n",
    "\n",
    "# Compute metrics\n",
    "metrics = []\n",
    "models = df_all_models[\"model\"].unique()\n",
    "\n",
    "for model_name in models:\n",
    "    df_model = df_all_models[df_all_models[\"model\"] == model_name]\n",
    "\n",
    "    # Keep only valid predictions and labels\n",
    "    df_model = df_model[\n",
    "        df_model[\"label\"].isin([\"correct\", \"incorrect\"])\n",
    "        & df_model[\"true_label\"].isin([\"correct\", \"incorrect\"])\n",
    "    ]\n",
    "\n",
    "    # Use real ground truth, given we added some incorrect examples\n",
    "    true_labels = df_model[\"true_label\"].tolist()\n",
    "    pred_labels = df_model[\"label\"].tolist()\n",
    "\n",
    "    accuracy = accuracy_score(true_labels, pred_labels)\n",
    "    precision = precision_score(true_labels, pred_labels, pos_label=\"correct\", zero_division=0)\n",
    "    recall = recall_score(true_labels, pred_labels, pos_label=\"correct\", zero_division=0)\n",
    "    f1 = f1_score(true_labels, pred_labels, pos_label=\"correct\", zero_division=0)\n",
    "\n",
    "    metrics.append(\n",
    "        {\n",
    "            \"Model\": model_name,\n",
    "            \"Accuracy\": accuracy,\n",
    "            \"Precision\": precision,\n",
    "            \"Recall\": recall,\n",
    "            \"F1 Score\": f1,\n",
    "        }\n",
    "    )\n",
    "\n",
    "# Create dataframe and sort it\n",
    "df_metrics = pd.DataFrame(metrics)\n",
    "df_metrics_sorted = df_metrics.sort_values(\"F1 Score\", ascending=False)\n",
    "\n",
    "# Preserve order of models for plotting\n",
    "model_order = df_metrics_sorted[\"Model\"].tolist()\n",
    "\n",
    "# Plot with fixed order\n",
    "plt.figure(figsize=(10, 6))\n",
    "ax = sns.barplot(\n",
    "    data=df_metrics_sorted, x=\"F1 Score\", y=\"Model\", palette=\"Blues_d\", order=model_order\n",
    ")\n",
    "plt.title(\"F1 Score by Model\")\n",
    "plt.xlim(0, 1)\n",
    "\n",
    "# Add labels at correct y-axis positions\n",
    "for i, model in enumerate(model_order):\n",
    "    score = df_metrics_sorted[df_metrics_sorted[\"Model\"] == model][\"F1 Score\"].values[0]\n",
    "    ax.text(score + 0.01, i, f\"{score:.2f}\", va=\"center\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# ---- Generate agreement Matrix for models -------\n",
    "\n",
    "# Generate a consistent ID for each example\n",
    "df_all_models[\"example_id\"] = df_all_models.groupby(\"model\").cumcount()\n",
    "\n",
    "# Pivot to wide format: one row per example, one column per model\n",
    "df_pivot = df_all_models.pivot(index=\"example_id\", columns=\"model\", values=\"label\")\n",
    "\n",
    "# Compute agreement rates between models\n",
    "agreement_matrix = pd.DataFrame(index=model_order, columns=model_order)\n",
    "\n",
    "for m1 in model_order:\n",
    "    for m2 in model_order:\n",
    "        agreement = (df_pivot[m1] == df_pivot[m2]).mean()\n",
    "        agreement_matrix.loc[m1, m2] = agreement\n",
    "\n",
    "agreement_matrix = agreement_matrix.astype(float)\n",
    "\n",
    "# ----------------------------------------\n",
    "# Plot Agreement Heatmap\n",
    "# ----------------------------------------\n",
    "\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.heatmap(agreement_matrix, annot=True, cmap=\"Blues\", fmt=\".2f\", cbar=True)\n",
    "plt.title(\"Model Agreement Matrix (Label Agreement Rate)\")\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# ---------------- Confusion Matrix for GPT-4o ----------------\n",
    "\n",
    "# Filter to GPT-4o predictions and valid labels\n",
    "df_4o = df_all_models[\n",
    "    (df_all_models[\"model\"] == \"gpt-4o\")\n",
    "    & (df_all_models[\"label\"].isin([\"correct\", \"incorrect\"]))\n",
    "    & (df_all_models[\"true_label\"].isin([\"correct\", \"incorrect\"]))\n",
    "]\n",
    "\n",
    "true_labels_4o = df_4o[\"true_label\"].tolist()\n",
    "pred_labels_4o = df_4o[\"label\"].tolist()\n",
    "rails = [\"correct\", \"incorrect\"]  # class order\n",
    "\n",
    "# Generate and plot confusion matrix\n",
    "confusion_matrix_4o = ConfusionMatrix(\n",
    "    actual_vector=true_labels_4o,\n",
    "    predict_vector=pred_labels_4o,\n",
    "    classes=rails,\n",
    ")\n",
    "confusion_matrix_4o.plot(\n",
    "    cmap=plt.colormaps[\"Blues\"],\n",
    "    number_label=True,\n",
    "    normalized=True,\n",
    ")\n",
    "plt.title(\"GPT-4o Confusion Matrix\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
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